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Methodological analysis demonstrates an interactive classification model for clinicians, suggesting human intuition combined with computational weighting enhances decision-making.
The computer poses intriguing challenges about the ways patient data may best be presented to aid clinicians. The authors present a classification approach which depends heavily on the clinician's unique ability to make meaningful hypotheses, based partly on hunches. After he sets up guidelines for establishing categories, the computer provides him with information about previous cases; if the optimal weights appear to possess reasonable validity he asks for a prediction about potential decisions concerning a current patient.
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GLUECK et al. (1969) studied this question.
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