Intelligent Computer-Aided Instruction for Medical Diagnosis

AI Classics/files/AI/classics/Clancey_Shortliffe/Ch11.pdf 

This chapter briefly outlines the difference between traditional instructional programs and ICAI. It then illustrates how GUIDON makes contributions in areas important to medical CAl: interacting with the student in a mixed-initiative dialogue (including the problems of feedback and realism), teaching problem-solving strategies, and assembling a computerbased curriculum. In evaluating GUIDON's performance, one can see the value in the basic idea of formalizing teaching knowledge in procedures that are separate from the knowledge to be taught. However, the program is inherently limited by the MYCIN knowledge base. The rule set is poorly structured, does not contain pathophysiological knowledge for justifying the diagnostic associations, and does not explicitly state the strategies for gathering information and focusing on hypotheses.

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