Ppt Birthday Templates

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					                                                                                        Outline
                                                          • Problem of information overload
                                                          • How to reason with/about time
                      Monitoring                          • Interpreting temporal data

                      6.872/HST950

                      Peter Szolovits




                          Problem                                           Time is Critical
• ICU alarms sound roughly every 30                       • Some systems have no explicit representation of
                                                            time
  seconds, in a typical (full) ICU
                                                             – E.g., Internist
• Nurse takes ~minutes to resolve alarm                          • <ABDOMEN TRAUMA RECENT>
                                                                 • <ABDOMEN TRAUMA REMOTE HX>
• How to resolve?                                                • <CHEST PAIN SUBSTERNAL LASTING GTR THAN 20
                                                                   MINUTE <S>>
  – Ignore (turn off) alarms                                     • <CHEST PAIN SUBSTERNAL LASTING LESS THAN 20
  – Prioritize                                                     MINUTE <S>>

  – Automate                                              • No representation of these pairs being “the
                                                            same,” but at different times.
  – Make alarming algorithms more intelligent             • Note: Same problem with space; need orthogonality!




 Motivating Example: Distinguishing Four
          Possible Relationships                                Even Simple Models Help
   Between Transfusion and Jaundice
                  ?
                           abdominal
                              pain
                                                          • PIP’s temporal model:
       blood                                                 – PAST, RECENT, NOW, SOON, FUTURE
    transfusion
                      ?
                                                          • Example:
                            jaundice                         – in “chronic glomerulonephritis” model, “past acute
                                                               GN”
• Post-transfusion antigen incompatibility
                                                             – (to my surprise), program hypothesized “future
  hemolytic anemia                                             chronic GN” after diagnosing “now acute GN”
• Post-Transfusion Hepatitis B: Acute Hepatitis
                                                                              AGN                      CGN
• G-6-PD hemolytic anemia treated by transfusion
• Post-Transfusion Hepatitis B: Chronic Active                                   past                  present      future
                                                   past                       present                  future




                                                                                                                             1
                      What is Time?                                                                Continuous View
                                                                                  d 2x
                                                                                        = −g
                                                                                  dt 2
• (Macroscopically) unidirectional                                                dx
                                                                                       = − gt + v 0
• Related to causality                                                            dt
• May be modeled in various ways                                                  x = − gt 2 + v 0 t + x 0

    – Continuous quantity, as in differential                                     • Differential equation view of world
      equations
    – Discrete time points, as in discrete event                                  • States (state variables) evolve according
      simulations                                                                   to their laws
    – Intervals, as in ordinary descriptions of
      durations, processes, etc.
    … or combinations




               Discrete Event View                                                     What Can Be a Time Point?
• Designated (countable) time points                                              • Calendrical point—a specific date/time
• Nothing “interesting” between events                                            • Recognizable event—e.g., “when I had my
• Events may be defined by                                                          tonsils out,” or “start of high school,” or
    – Clock “ticks”                                                                 “my ninth birthday”
    – Interactions among objects in universe                                      • Now—special, because it moves
    – Distinguished points in representation of state
      variables (e.g., highest point of cannon shell)




        Discrete Events are                                                                   Constraint Propagation
  Associated with State Transitions                                                            among Time Points
E.g., Beck & Pauker’s model to help compute quality-adjusted years of survival:                                            B   l, u
                                                                                                             l, u

                                                                                                        A           l, u              C


                                                                                  •   Clearly, T(A,B)+T(B,C) = T(A,C)
                                                                                  •   But we only know lower/upper bounds on T
                                                                                  •   L(A,C) = L(A,B)+L(B,C)
                                                                                  •   U(A,C) = U(A,B)+U(B,C)
                                                                                  •   and thus, we can infer relationships




                                                                                                                                          2
                                                                                                        Intervals and Points are
       Interval “Overlaps” in TUPese                                                                   Alternate Representations
                      +                   <ANOREXIA
                                                                                                • “Overlaps” defined in terms of its
                          ε                                                                       endpoints:
<IRRITABILITY
                     ´
                     +                                         Most medical history
                                                                 temporal terminology                                                          +0,+∞
                              +                                  is expressible in                                      <Anorexia                               Anorexia>
                          ´
                          +
                +                                       +        statements composed                                                      +ε,+∞
                                                        +0
                +0
                                  ´
                                  -   ε                          from TUP assertions.
                                                                                                           +ε,+∞                                     +ε,+∞
                                  -
                                                                                                                                      +ε,+∞
                     IRRITABILITY>
                                               +
                                                                 ANOREXIA>                                                   +0,+∞
                                               +´   ε                                               <Irritability                             Irritability>




                     Initial Assertions                                                                                 Constraint
• Completing                                                 <ANOREXIA

  all the                                                                                                                      <ANOREXIA
  relations not                                 3 DAYS                     4 DAYS

  explicitly                                    2 DAYS                     3 DAYS

  asserted                                                       7 DAYS                                             3 DAYS                          3 DAYS
                                  <IRRITABILITY                                     ANOREXIA>
                                                                 5 DAYS                                             2 DAYS                          3 DAYS


                                      Legend                                                                                         5 DAYS
                                                                                                 <IRRITABILITY                                                ANOREXIA>
                                                             Inferred                                                                5 DAYS

                                                             Externally asserted




          Propagated Constraint                                                                 Forms of Temporal Uncertainty
                                           <ANOREXIA                                            • Lower/upper
                                                                                                  bounds on temporal
                          2 DAYS                               3 DAYS
                                                                                                  distances
                          2 DAYS
                                                                3 DAYS                          • Central range +
                                                                                                  fringe
                                               5 DAYS
         <IRRITABILITY
                                               5 DAYS
                                                                        ANOREXIA>               • Continuous
       • Order n2 edges in fully interconnected graph                                             distributions
       • Order n3 computation
       • Work to localize propagation to semantically
         related events




                                                                                                                                                                            3
               Interval View                                     Allen’s Temporal Intervals
• Activities, processes take place over
  extended intervals of time
• Observations are true over periods of time
• Systems remain in steady (from some
  viewpoints) states over intervals




       Inference among Intervals                                Temporal Control Structure.
             by Composition                                             - T. Russ
             Y-Z

                        e.g., if A starts B and B overlaps C,
                        what are the possible relationships
                          between A and C?
                        1. A before C
X-Y
                        2. A meets C
                        3. A overlaps C




                                                                • Processes maintaining truth of abstractions over
                                                                  specified interval
                                                                • Update of past beliefs from corrections or new data.
                                                                • Actions are permanent.




           Back to Monitoring                                   “Two-Point” Trend Detectors
•   Detecting Trends                                            • Restricted to hospitals with the most
•   Language for Trend Description                                complete information systems
•   Matching algorithms                                         • Rind & Safran, 1992
•   Top-down vs. bottom-up vs. both                             • Two point event detector
                                                                  – rise in creatinine > 0.5 mg/dl
•   Learning trend detectors
                                                                • Therapeutic context
                                                                  – Renally cleared or nephrotoxic medication
                                                                  – Possible care providers
                                                                • Implementation
                                                                  – M procedures linked to E-mail




                                                                                                                         4
        BIH Experience (cont’d)                                                                      Are these two-point trend
• Time series trial                                                                                    detectors sufficient?
• 607 in 348
  admissions during                                                                         •    If not, why not?
  control periods
• 497 events in                                                                             •    Noisy data.
  intervention period
• 369 alerts, sent to
                                                                                            •    Multi-phased processes.
  584 different
  physicians, 9.25
                                                                                            •    Uncertainty over time.
  recipients per alert                                                                      •    Uncertainty over values.
• Improved response
  time
• Improved outcomes

                                      Representation
                                    Easily implemented as an Arden Syntax
                                    MLM




                                                                                            Pediatric Growth
                                                                                            Pediatric Growth
         Issues in Trend Detection                                                          Monitoring
                                                                                             Monitoring
                                                                                                 • Data:
 • Defining significant trends                                                                     - heights, weights
   – Multiple variables                                                                            - family history
   – Multiple phases                                                                               - bone ages
   – Temporal and value uncertainty                                                                - pubertal data,
                                                                                                   stages
 • Detecting trends from data                                                                      - hormone values
 • Generating alarms                                                                             • Disorders show
                                                                                                   characteristic
 • Displaying, explaining results                                                                  patterns on growth
                                                                                                   chart.
 • Changing clinical context                                                                                                       Boy with constitutional
                                                                                                                                   delay
                                                                                            --Haimowitz




  Curve Fitting Approach                                                                     Describing Average Normal Growth
                                                                                             Describing Average Normal Growth

                      a1                                                                     •   Def. Z-score ≡ Number of standard deviations a patient's
                                                                                                 parameter is from the mean for that age.
                                                    a                        a
Height(t) = + e -b             (t - c1)
                                          +           2            +           3             •   From birth until age 2 - 3 years, height and weight vary
          1                1                  1 + e -b2 (t - c2)       1 + e -b3 (t - c3)
                                                                                                 together and establish baseline Z-scores.
                                          Triple-logistic curve [Thissen and Bock
                                          1990]                                              •   From then until onset of puberty, height and weight
                                                                                                 maintain approximately the same Z-scores.
  ak = component k’s contribution to mature stature
  bk = a parameter proportional to the maximum growth velocity of the                        •   Throughout this time, bone age is approximately equal to
  component (maximum rate of growth is (a * b) /4 centimeters per year)                          chronological age.
  ck = the age in years at which the maximum growth velocity occurs




                                                                                                                                                             5
  Trend Template for
  Trend Template for
  Male Average Normal Growth
  Male Average Normal Growth                                                                                         Trend Template, continued
                                                                                                                     Trend Template, continued
                                                                                                                     Landmark points
                                                                                                                           Time constraints
  Landmark points
                                                                                                                     Intervals
         Time                                                                             Ht
         constraints            Ht Z-score Ht Z-score Wt Z-score         Ht                                                Time constraints
                               - Wt Z-score
                                                                                                                           Value
  Intervals                                                                    Peak Ht           Growth                    constraints
                                                            Puberty
                                                             onset              veloc             stops
         Time                 Birth
                                                                                                                                      Ht Z-score Wt Z-score                       Ht
         constraints                                                                                                                                               Ht
                               0       2     3             10       13        12.5    14.5     17         19 Age
                                                                                                                           Ht Z-score
         Value
                                                                                                                          - Wt Z-score
         constraints
                                              Chron. age
                                                                                                 Growth
                              Birth           - bone age
                                                                                                  stops                                                                 Peak height      Growth
                                              0                                                                                                        Puberty                           stops
                                                                                                                      Birth                             onset            velocity
                                       Pubertal
                                        stage                                 Pubertal         Pubertal
                              Birth                             Pubertal       stage   Pubertal stage
                                        1                        stage                  stage
                                                                                                                                                                                 14.5             Age
                                                                2
                                                                              3                 5                     0            2          3       10      13        12.5            17   19
                                                                                        4
                                                                                                    Growth
                                                           Puberty
                                                            onset                                    stops




 Trend Template, continued
 Trend Template, continued                                                                                         Value Constraints Have Regression Models
                                                                                                                   Value Constraints Have Regression Models
 Landmark points
                                                                                                                                                    Constant                   Linear
       Time
                                                                                                                     • Low-order                    f(D)t = K + εt
       constraints                                                                                                                                                             f(D)t = a t + b + εt
 Intervals                                                                                                           polynomials
      Time                                  Chron. age
      constraints                           - bone age
                                                                                                                     • Parameter estimates:
 BirthValue                                    0                                                                     quantitative or
      constraints                                                                                                    qualitative
                                                                         Growth
                Pubertal                                                  stops                                                                    Quadratic
                 stage                            Pubertal
 Birth                                                     Pubertal
               1
                                   Pubertal        stage
                                                            stage
                                                                                                                                                   f(D)t = a t 2 + b t + c + εt
                                    stage         3                 Pubertal
                                    2                      4         stage
  0                                                                 5
                           Puberty
                            onset                                                              Growth
                                                                           11.5 14.5            stops




 Goodness of Fit of a Hypotheses
 Goodness of Fit of a Hypotheses                                                                                                                  TrenDx
                                                                                                                                                  TrenDx
                                                                                               Least-Squared          •   Matches process data to trend templates.
                                                 Value Constraint                              Error Line
   Mean Absolute
    % Error                                                                                                           •   Optimizes over alternate trend
                                                                                                                          chronologies.
         Σ
                   Yt - Y’t                                                       Y’t
                                                                                                                      •   Compares best matches of competing
   =       t        Yt
                                                                                     Yt
                                                                                                                          trends within same clinical context.
         N - (no. estim. pars.)

•Hypothesis score is weighted average of value constraint
scores.




                                                                                                                                                                                                        6
  Linking Patient Data to Trend Template
  Linking Patient Data to Trend Template                                                              Processing height and weight, 2.1 years
                                                                                                      Processing height and weight, 2.1 years
                                                                     Temporal Utility Package          • Branch to two hypotheses of average normal
                    Patient-1     Patient-1                            [Kohane 1987]                     growth:
                    Date of Birth Height
                    3/17/1992     4/28/1994

                                                                                                                  Ht Wt                                            Ht Wt
 Patient Data                                                                                                     2.1 2.1                                          2.1 2.1
 Trend Template                                                      Puberty                          (1)         Int1
                                                                                                                                                (2)
                                                                      onset                                                          Int2             Int1               Int2
             Birth                                                                                                                                           2   2.1
                                                                                                                     2.1         3
                      0              2          3                                               Age
                                                                    10         13

                             Int1
                                                                Int2




  Processing data through age 4.1
  Processing data through age 4.1                                                                      Maximizing Chronologies for a Trend
                                                                                                       Maximizing Chronologies for a Trend
•First hypothesis has lower error.                                                                     Data: D1 D2 ... Dt-1 Dt
•Refining patient history from population pattern and data.                                                       time

                                                                                                      TT normal - Chron1         TT normal - Chron2      TT normal - Chron3
          Ht Wt           Ht Wt Ht Wt                                      Ht WtHt Wt Ht Wt                              0.052                0.043                    0.055
          2.1 2.1         3.1 3.1 4.1 41                                   2.1 2.1 3.1 3.1 4.1 41
  (1)     Int1
                                                    (2)
                                Int2                                Int1                      Int2
             2.1 + ε        3                                              2        2.1 - ε           0.063       0.048          0.056      0.033       0.045    0.069     0.072

             Score: 0.14                                     Score: 0.37

                                                                                                                                 Beam search




Beam search -- soundness vs. efficiency
Beam search soundness vs. efficiency                                                                   Diagnostic Monitoring Framework
                                                                                                       Diagnostic Monitoring Framework
                                                                                                        •   Clinical context
                                 Noise?                         Actual                                        •   Partition of trend templates
                                                                transition?                                   •   One normal; others faulty
        Data:        1 1 1                                                                                    •   TrenDx concurrently matches to same process data
                1          2             22 2
                                 2                  2
                                     2
                                                                                                        •   Compare best matching hypothesis of
                                                        2
                                                            2                                               each trend template
                    Constant                                    2
                                                                                                        •   Significant faulty trend match triggers
                                                            Linear (D1 -)
             Phase 1                                                                                        actions
                                                        Phase 2                                               •   Alarms
                                                                                                              •   Displays
                                                                                                              •   Other clinical contexts




                                                                                                                                                                                   7
                       TrenDx Results on Growth Patient
                       TrenDx Results on Growth Patient
                                                        Boy with constitutional
                                                          Patient 39, Const. Delay
                                                                                                                                                                                                          Exploratory Clinical Trial
                                                                                                                                                                                                          Exploratory Clinical Trial
                   0.5                                  delay
                                                                                                                                                                                                     •    30 growth records from Children’s Hospital
                  0.45                                                                                                                                                      H                             Endocrinology Clinic
                                   B Normal
                                   J Cons Delay                                                                                                                                                            •   26 have disorders; 4 normals.
                   0.4
                                   H Early Puberty
                  0.35
                                                                                                                                                                                                     •    20 growth records from general pediatrician
                                                                                                                                                                            B                              •   All 20 declared normal
Score (% error)




                   0.3
                                                                                                                                                        B
                                                                                                                                                                                                     •    Alarm based on (TTF - TTN)
                  0.25                                                                                                                                  H
                                                                                                                                                                    H
                                                                                                                                                                    B       J                              •   Single wide gap
                   0.2
                                                                                                                                                        J
                                                                                                                                                                    J                                      •   Persistent narrower gap
                                                                                                                                              J
                  0.15
                                                                                                         H           H
                                                                                                                     B          H
                                                                                                                                B
                                                                                                                                J
                                                                                                                                            J
                                                                                                                                            B B
                                                                                                                                            H H                                                                                                    Constitutional delay Early puberty
                                                                      H                       H          B           J
                                                                      B                       B          J
                   0.1
                                                                                              J                                                                                                          Sensitivity                                               .52                                                              .67
                                                                      J
                  0.05
                                                                                                                                                                                                         Specificity                                               .96                                                              .75
                       0                      H
                                              J
                                              B         H
                                                        J
                                                        B
                           0                  2                       4                       6         8                                  10                      12                        14
                                                                                              Age (years)




                  Intensive Care Unit Monitoring
                  Intensive Care Unit Monitoring                                                                                                                                                  TrenDx Matching to Handbagging Case
                                                                                                                                                                                                  TrenDx Matching to Handbagging Case
                                                                                        B
                                                                                                                                                                                                                                                                                                        B
                                                                                                                                                                                                                                         190
              190                                                                                                                                                                                                                                                                                                 B B               B B B B B
                                                                                                                                                                                                                                                                                                                                              B                    B        B            B
                                                                             B                                                                                                                                                                                  B B           B               B B           B B B
                                                                      B BBB B B B B B B B
                                                                                                                                                                                                                                                                                          B
                                                                         BB                                                                                                                                                              170
                       BB B B B
                           B                 BB B B    B B B BB B B B B
                                                                    B
                                            BB B BB B B BBBBB BB B B BB
                                                                                        BB B B B B BBB B
                                                                                                  B BB                                                      BBB
                                                                                                                                                             BB          BB BB B
                                                                                                                                                                        BB B BB B B
                                                                                                                                                                                                                                                           J       Mean Art BP
                       BB B BB B                                                                      B
                                                                                                                                                                                                                                         150               1       FIO2
              170
                                                                                                                                                                                                  Hemodynamic                            130
                                                                                                                                                                                                                                                           H       O2 Saturation



              150
                                                                                                                                                B      ECG HR                                      fault                                 110
                                                                                                                                                                                                                                                           B       ECG Heart Rate


                                                                                                                                                J      Mean Art BP
                                                                                                                                                H      O2 Saturation
                                                                                                                                                                                                   becomes                                 90      H
                                                                                                                                                                                                                                                                   1
                                                                                                                                                                                                                                                                   H
                                                                                                                                                                                                                                                                          H
                                                                                                                                                                                                                                                                              H H                           H                                                  H                                  H



              130
                                                                                                                                               1       FIO2
                                                                                                                                                                                                   significant                             70          J                  J       J       J J           J   J       J   J     J J   J   J    J   J
                                                                                                                                                                                                                                                                                                                                                       J   J   J
                                                                                                                                                                                                   trend.                                  50
                                                                                                                                                                                                                                           12:20 AM            12:22 AM                 12:24 AM                  12:26 AM                  12:28 AM
                                                                                                                                                                                                                                                                                                                                                                   J        J
                                                                                                                                                                                                                                                                                                                                                                       12:30 AM
                                                                                                                                                                                                                                                                                                                                                                                     J
                                                                                                                                                                                                                                                                                                                                                                                         1
                                                                                                                                                                                                                                                                                                                                                                                             J
                                                                                                                                                                                                                                                                                                                                                                                                 12:32 AM

              110                                                                                                                                                                                                                       0.04
                                                                                                                                                                                                                                                                                                                                                                                     B
                                                                              1H
                                                                               H         H          H       HH
                                                                                                             HHH H H H H
                                                                                                                        H HH H
                                                                                                                       H HH HH HH
                                                                                                                                H H
                                                                                                                                                                                                                                       0.035                   B       Adequate Handbagging
                                                                                                                                                                                                                                                                       Hemodynamic Fault
                               H                                                  H                           H  H               H                                                                                                                             J                                                                                                            B    B
                  90           H                 H          HH
                                                            HH        H
                                                                      HH                                              H             H                             H HH H H H H
                                                                                                                                                                  H HHH HH                                                              0.03
                                                                                                                                                                                                                                                               H       Difference
                                                                                  H                                                                                                                                                                                                                                                                                B    B
                                                                                                                                                                                                                     Score (% Error)




                                                                                                                                                                                                                                       0.025                                                                                                                                         H
                                                                 JJ                                                                                                                                                                                                                                                                                        B
                      JJ J     JJJJ JJJJ    JJJ JJ J JJJJJ JJJ            JJJ J
                                                                                                                                                                                                                                                                                                                                                               B
                  70 J J                                                          J J JJ JJ JJJJ                                          JJJJJJJ J J                     J J J J J J JJJJ                                              0.02                                                                                                                                H H
                                                                                                                                                 J J J J J J J J J JJJJ JJ JJ J J J J J
                                                                                                                                                                                                                                                                                                                                                      B
                                                                                                JJJJ                                JJ JJ                                                                                                                                                               B
                                                                                                                                                                                                                                                                                                        J
                                                                                                                                                                                                                                                                                                                                             B B
                                                                                                                               J JJJ J                J J JJ J J J J                                                                                                                                        B B                       B
                                                                                                                           JJ J                                                                                                        0.015                                                                J J     B B
                                                                                                                                                                                                                                                                                                                    J J       B B   B
                                                                                                    J                                                                                                                                                                                                                         J J   J J               J    J
                                                                                                                J JJ JJJJJ
                                                                                                                                                                                                                                                                                                                                             J   J               H H
                                                                                                     JJJ                                                                                                                                                                                                                                                       J J J J               J
                                                                                                         J J JJ                                                                                                                         0.01                                                                                                                   H
                                                                                                                                                                                                                                                                                                                                                                                 J
                   50
                  12:00 AM                 12:10 AM              12:20 AM
                                                                                                        1
                                                                                                  12:30 AM                 12:40 AM                    12:50 AM                   01:00 AM                                                                                        J J
                                                                                                                                                                                                                                                                                  B B
                                                                                                                                                                                                                                                                                          B
                                                                                                                                                                                                                                                                                          J
                                                                                                                                                                                                                                                                                              B
                                                                                                                                                                                                                                                                                              J     B
                                                                                                                                                                                                                                                                                                    J                                                      H

                                                                                                                                                                                                                                       0.005                                  B
                                                                                                                                                                                                                                                                              J                                                                       H
                                                                                                                                                                                                                                                                                                                                                 H
                                                                                                                                                                                                                                                                                                                                        H H

        Hemodynamic fault during oxygen handbagging                                                                                                                                                                                            0
                                                                                                                                                                                                                                         12:20:00 AM
                                                                                                                                                                                                                                                                   H H H H H H H H H H H H H
                                                                                                                                                                                                                                                                   J J
                                                                                                                                                                                                                                                                   B B
                                                                                                                                                                                                                                                           12:22:00 AM
                                                                                                                                                                                                                                                                                             H H
                                                                                                                                                                                                                                                                                      12:24:00 AM               12:26:00 AM
                                                                                                                                                                                                                                                                                                                    Time
                                                                                                                                                                                                                                                                                                                                    H
                                                                                                                                                                                                                                                                                                                                        12:28:00 AM                12:30:00 AM               12:32:00 AM




                                                                                                                                                                                                     Long’s Signal Segmentation
                           Top-Down vs. Bottom-Up
                                                                                                                                                                                                              Algorithm
                                                                                                                                                                                                  • Goals:
                                                                                                                                                                                                     – Segment multiple data streams into a
                                                                                                                                                                                                       sequence of time intervals (cover time line)
                                                                                                                                                                                                     – Within each interval, characterize each signal
                                                                                                                                                                                                       by a (linear) regression line
                                                                                                                                                                                                     – Optimize for least total residual (greedy)
                                                                                                                                                                                                     – Parameter controls maximum tolerable error
                                                                                                                                                                                                           • Trades fitting error vs. number of segments




                                                                                                                                                                                                                                                                                                                                                                                                            8
         Segmentation                                Segmentation




         Segmentation                        Multiple Data Streams




Effect of Varying Sensitivity to Change


                                          Event Discovery in Medical
                                              Time-Series Data


                                                   Christine L. Tsien, Ph.D.
                                                     Harvard Medical School, Boston MA
                                              Massachusetts Institute of Technology, Cambridge MA




                                                                                                    9
                                                                            Observational Study of ICU
                            Overview
                                                                                     Alarms
 • Background: Intensive Care Unit (ICU)                                 • Prospective 10-wk study at Children’s Hospital
 • TrendFinder approach to event discovery                               • 2942 alarms; 298 hours
      – components                                                                                            8%
                                                                                                        6%
      – performance metrics
 • Applications: ICU signal artifacts, events
                                                                         • Problems
 • Summary                                                                  – Wider limits
                                                                                                                                           Alarm
                                                                                                                                           Types
                                                                            – Silenced alarms
                                                                            – Stress
                                                                                                                              86%




        TrendFinder Approach to                                             TrendFinder Application:
            Event Discovery                                               Detecting Events in the MICU
                                                                         • Event: clinically-relevant systolic BP alarms
                                                                         • Data collection (Children’s Hospital)
   Event
                 Annotated      Annotated
                                               Model       Performance      – 12 weeks
                   Data           Data
Identification
                 Collection   Preprocessing
                                              Derivation    Evaluation
                                                                            – 585 hours of 5-sec data
                                                                         • Prospective alarm annotations

                                                                                                 Annotated     Annotated
                                                                                   Event                                       Model         Performance
                                                                                                   Data           Data
                                                                                Identification                                Derivation      Evaluation
                                                                                                 Collection   Preprocessing




      Annotated Data Collection                                           Annotated Data Collection Program
               Setup
                  Patient

    Bedside           Bedside                 Bedside
                                     ...
    device 1          device 2                device n

                 Spacelabs
                 monitor                   Alarms

                  Laptop                 Trained
                  computer               observer




         Data files                    Annotations




                                                                                                                                                           10
Feature Attribute Derivation   Feature Attribute Derivation




Feature Attribute Derivation   Feature Attribute Derivation




      maximum = 10                   minimum = 7




Feature Attribute Derivation   Feature Attribute Derivation




      range = 3                      mean = 8.5




                                                              11
Feature Attribute Derivation         Feature Attribute Derivation




      median = 8.5                         slope = -1




Feature Attribute Derivation         Feature Attribute Derivation




      absolute value of slope = +1         standard deviation = 1.29




Feature Attribute Derivation         Feature Attribute Derivation




                                                                       12
Feature Attribute Derivation   Feature Attribute Derivation




Feature Attribute Derivation   Feature Attribute Derivation




Feature Attribute Derivation   Feature Attribute Derivation




                                                              13
    Feature Attribute Derivation                                Feature Attribute Derivation




    Feature Attribute Derivation                                Feature Attribute Derivation




                                                              Example Decision Tree Model
                Model Derivation
                                                                for BP Artifact Detection
• Data
   – labeled feature vectors of derived values
                                                        bp_med3 <= 4: artifact (114.0/3.0)
   – training, evaluation, test sets
                                                        bp_med3 > 4:
• Supervised machine learning methods                          bp_range3 <= 7: non-artifact (10959.0/72.5)
   – Decision trees (c4.5)                                     bp_range3 > 7:
   – Neural networks (LNKnet)                                           bp_med10 > 46: non-artifact (126.0/23.7)
   – Logistic regression (JMP)                                          bp_med10 <= 46:
                                                                                  bp_std_dev3 <= 5.51: non-artifact (78.0/28.5)
• Models: labels previously unseen feature vectors as                             bp_std_dev3 > 5.51:
  event or non-event                                                                       co2_low10 <= 5.3: artifact (46.0/10.1)
                                                                                           co2_low10 > 5.3:
                                                                                                   hr_high5 <= 157: non-artifact (27.0/12.8)
                                                                                                   hr_high5 > 157: artifact (21.0/8.2)




                                                                                                                                               14
If temporal representation provides                                                            Time series: Arterial BP and HbO2
 leverage in reasoning over time...
• What temporal representation have we                                                         50
                                                                                                                                                                                           ABP

  overlooked?                                                                            g
                                                                                           40

                                                                                         H 30
                                                                                         m
                                                                                         m 20

                                                                                               10
                                                                                                 0                 5                      10                    15            20            25

                                                                                           0.01
                                                                                                                                                                                          HbO2
                                                                                         0.005
                                                                                   .
                                                                                   U           0
                                                                                   .
                                                                                   A
                                                                                         -0.005

                                                                                          -0.01
                                                                                                  0                5                      10                    15            20            25
                                                                                                                                                seconds




                                   Methods                                                                  Frequency Domain
          Fourier transformation: translation from the
          time domain to the frequency domain.                                temp.                    baroreflex
                                                                                                                                                                RR                           pulse rate
 R to R
          (imaginary data)                                                         150                                                                                         80
                                                                              P
                                                                                                                                                                               60
                                                                              B    100
                                                                                                                                                                               40
          RR interval (s)




                                                                              D     50
                                                                              S                                                                                                20
                                                                              P
                                                                                    0                                                                                          0
                                                                                     0         0.05   0.1   0.15       0.2         0.25   0.3    0.35     0.4        0.45       0         1.25      2.5
                                                                                          -5                                                                                         -6
                                                                                      x 10                                                                                       x 10
                                                                               R    6                                                                                          3
                                                                               I
                                                                               N    4                                                                                          2

                                                                               D    2                                                                                          1
                                                                               S
                            Time                                               P    0                                                                                          0
                                                                                                                                                                                0         1.25      2.5
                                                                                     0         0.05   0.1   0.15       0.2         0.25   0.3    0.35     0.4        0.45
                                   (time)2/Hz




                            (s)                                                   0.06                                                                                      0.015

                                                                                  0.04                                                                                       0.01
                                                                             D
                                                                             S 0.02                                                                                         0.005
                                                                             C
                                                                                    0                                                                                          0
                                                                                     0         0.05   0.1   0.15       0.2         0.25   0.3   0.35      0.4        0.45       0         1.25      2.5

                                                      HIGH Frequency (Hz)                                                    Hz.                                                          Hz.
                                                LOW




 Opportunities of the frequency
                                                                                                                                   Summary
            domain
• For new kinds of alarms
                                                                            • Careful selection of temporal representations are
• Machine learning on different part of the                                   necessary to capture the aspect of interest of a
  feature space                                                               biological/clinical system.
                                                                            • Temporal reasoning programs have been developed but
• Informative displays                                                        are not widely used.
• Toolkit to focus on events with time-                                     • Trend detection with on-line data can be useful (low-
                                                                              hanging fruit)
  constants of interest
                                                                            • Much can be accomplished with simple 1 and 2 point trend
                                                                              detectors
                                                                            • Noisy data and medically complex trends require more
                                                                              sophisticated representation and reasoning mechanisms
                                                                                  – E.g. conversion into the frequency domain




                                                                                                                                                                                                          15

				
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