By Glenn D. Rennels M.D., Ph.D. (auth.)
As examine on professional platforms has moved good into its moment decade, it has develop into renowned to quote the constraints of the phenomenologic or associational method of wisdom illustration that was once regular of first iteration platforms. for instance, the Internist-1 wisdom base represents explicitly over six hundred ailments, encoding linked ailment manifestations (signs, indicators, actual findings, and lab abnormalities) yet failing to house the explanations that these findings should be found in the affliction [Miller, R. A. 82]. in recent times Pople has sought so as to add specified causal types to the information base in a revised model of this system often called CADUCEUS [Pople 82]. equally, a standard creation rule within the MYCIN process states inferences that could be drawn whilst particular stipulations are chanced on to be real [Buchanan 84], however the underlying reasons for such relationships aren't encoded. Clancey has argued that MYCIN wishes such "supporting wisdom" represented, specifically if its wisdom base is for use for instructing reasons [Clancey 83]. via the overdue Nineteen Seventies, synthetic intelligence researchers have been commencing to test with reasoning structures that used distinct mechanistic or causal niodels of the item being analyzed. among the finest early examples have been a application to coach scholars easy methods to learn digital circuits [Brown eighty two] and a process for diagnosing issues of mechanical units [Rieger 76].
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Additional resources for A Computational Model of Reasoning from the Clinical Literature
Medical evidence is such that most conclusions can be drawn only with a limited degree of certainty. This character of medical evidence and hypothesis assessment has driven AIM researchers to experiment with different scoring schemes. Few AIM systems have used classical probability theory to represent uncertainty. Systems developed in medical centers have tended to seek representations for uncertainty which reflect physician behavior, and several researchers have argued that probability theory and the use of Bayes' Theorem do not model that behavior well [Shortliffe 75].
Some preliminary research pr9jects [Hollenberg 84] are examining how systems might possess enough domain knowledge to help the user select appropriate branches for the decision tree: suggesting additional branches or identifying branches of the current model which do not make sense. As mentioned earlier, the clinical literature is often the source for the probabilities used in this type of program. The process of assessing the clinical literature is outside the scope of these programs however. The goal of the Roundsman project is to implement a computational model of this process.
3. 1. Bibliographic Retrieval Systems With the development of MEDLlNE, the National Library of Medicine (NLM) pioneered research into bibliographic retrieval. This work certainly demonstrated that research physicians could utilize computer-based assistance in searching the medical literature. Interest in this and subsequent systems such as BRS, DIALOG, and Paperchase [Horowitz 81] suggests that practicing clinicians recognize a similar need [Doszkocs 80]. Indeed, Scura demonstrated that the assistance of a clinical librarian to identify case-specific literature could effectively change management decisions [Scura 81].
A Computational Model of Reasoning from the Clinical Literature by Glenn D. Rennels M.D., Ph.D. (auth.)