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Preventive Medicine Professional diseases are still a major concern in medicine, in spite of the strict regulations most governments and companies are introducing to limit the impairment risk related to professional activities. The increasing average age of the workers as well as the increasing life standard puts new demands for limiting the risk of impairment at higher ages. Expert systems and decision- support systems help to reduce the work and time consumption for health condition screening and for assessing the professional health risks of workers subjected to high noise levels, noxious gases and fumes, or high levels of psychical stress. As an example, typical requirements for such a system used in assessing the risk of hearing loss include the ability to take into account a huge number of factors affecting hearing loss and the ability to determine the risk of specified levels of hearing loss after large time periods. Requirements also include the capability of processing fuzzy information presented by the physician (during examination, e.g., “the tympanum color is reddish”), or by an engineer when describing the nature of the noise (“the noise is impulsive,” “the average spectrum of the noise is close to that of the pink noise”). In addition, requirements include the ability to take into account additional risk factors that may increase the potential of hearing loss, such as mycelia in the atmosphere. Also in preventive medicine, various AI-based models and prediction tools successfully complement and compete with statistical tools today.
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