R4 Andy Aiken Overview The Refiner series Cognitive psychology of diagnosis Diagnosis Web Proposed work: R4 The Refiner Series Case-based system Cases are assigned to categories System generates descriptions of these categories Resolves inconsistencies in datasets An inconsistency is when a case does not only match the category it has been assigned to by an expert User-directed The Refiner Series History Refiner:initial system (1988) Refiner+: batch system (1995) Much more efficient Refiner++: current version Java, faster, more strategies and data types, GUI Evolution not revolution The Refiner Series The Refiner Series Refiner++ was shown to experts Anaesthetics,child psychology, HDU, medical CAL, engineering Reaction was generally positive System to be used in several proposed interdisciplinary projects BUT… The Refiner Series Limitations Time Series Many medical datasets, for example, are time- series data Noise Can deal with noise, but in a limited and sometimes confusing way This is our focus Refiner and Noise What changes are needed? Changes the focus of the system Refiner++: the creation of category descriptions R4: classification This requires us to investigate the science of diagnosis Diagnosis How do clinicians perform diagnosis? How is it taught? What is the cognitive psychology? Diagnosis Differential Diagnosis What is a differential diagnosis? Requires the diagnostician to memorise a vast amount of information Simplistic view of the process Diagnosis Diagnosis Hypothetico-Deductive Reasoning Uses both forward and backward chaining Iterative Requires significant cognitive processing Diagnosis Given initial facts, work forward to likely hypotheses These are the differential diagnoses Facts Hypotheses Diagnosis Identify other facts which should be present for these hypotheses to hold, and investigate them Can attempt to distinguish between a set Facts Hypotheses of competing hypotheses, or get additional confirmation for a hypothesis Diagnosis Repeat until satisfied One hypothesis is notably more likely than others One likely hypothesis Facts Hypotheses is especially significant The courses of action are similar Diagnosis The effect of expertise Novices perform HDR, but the process is slow, potentially incomplete and inaccurate Intermediates perform HDR, but this is still a slow process Experts still perform HDR but this is supplemented by compiled knowledge (shortcuts; faster) Diagnosis Illness Scripts (Feltovich, 1984) Compiledknowledge used in diagnosis Comprises three knowledge sources: Faults Consequences Enabling conditions Says nothing about how they are used Diagnosis Faults Theunderlying malfunctions which give rise to the symptoms Consequences Detectable signs and symptoms Enabling conditions Background knowledge Predisposing factors (patient’s case history) Boundary conditions (age and gender) Hereditary factors Diagnosis Illness scripts don’t explain the process of diagnosis Diagnosis Web A more inclusive explanation More knowledge sources Links between them indicate processes Diagnosis Web Courses of Action Hypotheses Cases Contextual Faults Factors Descriptors Features Diagnosis Web How do we use the diagnosis web to improve the Refiner series? R4 Will be aimed at novice diagnosticians Medical students, but not limited to medical domains An aid to diagnosis Supports the student’s reasoning without taking over R4 Three stories: An aid to diagnosis Scaffolding user’s diagnostic skill Generation of test cases R4 User presents a case to the system The system displays two lists: Likely (differential) diagnoses Potential next steps (descriptors to find values for) to hone in on the correct diagnosis Providing more data for the case updates these lists automatically DXplain DXplain Used by clinicians to perform diagnosis User enters findings, system updates lists of likely diagnoses and other findings to be investigated Sound familiar? R4 and DXplain (et al) Superficially very similar R4 is case-based; others are database-driven Easier to create & maintain a casebase R4 uses descriptor values; others are term- based Lends itself to automation No other system attempts to mirror the cognitive process of diagnosis Conclusion Refiner++ was well received but did not handle noisy datasets well Adding the facility to handle noisy datasets changes the focus to classification Combining HDR and illness scripts leads to the Diagnosis Web The new Refiner system will incorporate aspects of HDR and illness scripts to mirror how diagnosis is performed Questions?
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