Knowledge bases in medicine: a review.
Efforts to represent knowledge effectively have been central to progress in various aspects of medical informatics. These efforts range from relatively simple "electronic textbooks" to fairly sophisticated knowledge-based systems, which function as well as, or even better than, human experts faced with similar problems. Knowledge bases have been developed in many fields, but the relatively limited domains and structured language of medicine, as well as the importance of information in the provision of good medical care, have made research in medical knowledge representation an area of intense activity. This paper reviews representative knowledge bases and knowledge-based systems in medicine: electronic textbooks such as PDQ and the Hepatitis Knowledge Base (HKB), rule-based systems such as MYCIN, causal models (e.g., CASNET), and hypothesis- or frame-based systems, exemplified by PIP and INTERNIST-1. The paper describes the relationships among divergent approaches and provides a sense of current and future trends. It examines problems in knowledge-based systems, particularly in knowledge representation and acquisition, and the responses to these challenges. The latter include the use of domain-independent software shells for constructing knowledge bases, the adaptation and use of previously existing knowledge bases, and multiple uses of the same knowledge base for different purposes.
Reference Department, New York Academy of Medicine Library, New York 10029.
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D001185:Artificial Intelligence; D005103:Expert Systems; D009862:Online Systems; D014481:United States