Medicine, ai in
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abstract: This article describes the theoretical basis and current research themes of the field of artificial intelligence in medicine (AIM). Medical advice systems were first envisioned in the late 1950s; more than thirty years later, systems have been built in numerous medical domains, using a wealth of modeling and reasoning techniques. We briefly discuss: the use of protocol analysis in the development of theories of medical problem solving; the nature of medical knowledge; taxonomies of biomedical concepts; knowledge structures; inference and control methods for medical reasoning; uncertainty management; and evaluation functions. Research themes we address include: knowledge acquisition; decision-theoretic approaches; causal reasoning; temporal reasoning and planning; strategies for the diagnosis of multiple diseases; explanation and critiquing; and validation and evaluation of medical expert systems. Finally, the issues and themes we describe are illustrated in the context of several AIM programs--QMR, Pathfinder/Intellipath, and ONCOCIN--that have achieved limited clinical use.
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| Abstract | This article describes the theoretical bas … This article describes the theoretical basis and current research themes of the field of artificial intelligence in medicine (AIM). Medical advice systems were first envisioned in the late 1950s; more than thirty years later, systems have been built in numerous medical domains, using a wealth of modeling and reasoning techniques. We briefly discuss: the use of protocol analysis in the development of theories of medical problem solving; the nature of medical knowledge; taxonomies of biomedical concepts; knowledge structures; inference and control methods for medical reasoning; uncertainty management; and evaluation functions. Research themes we address include: knowledge acquisition; decision-theoretic approaches; causal reasoning; temporal reasoning and planning; strategies for the diagnosis of multiple diseases; explanation and critiquing; and validation and evaluation of medical expert systems. Finally, the issues and themes we describe are illustrated in the context of several AIM programs--QMR, Pathfinder/Intellipath, and ONCOCIN--that have achieved limited clinical use. --that have achieved limited clinical use. |
| Address | Stanford, CA, USA + |
| Author | Adam Galper +, Glenn D. Rennels +, Edward H. Shortliffe +, and Ramesh S. Patil + |
| Bibtype | techreport + |
| Institution | Knowledge Systems, AI Laboratory + |
| Key | KSL-90-37 + |
| Month | April + |
| Number | KSL-90-37 + |
| Tag | Computer science + |
| Title | Medicine, AI in + |
| Tr id | KSL-90-37 + |
| Year | 1992 + |
