KNOWLEDGE ENGINEERING FOR MEDICAL DECISION-MAKING - REVIEW OF COMPUTER-BASED CLINICAL DECISION AIDS

被引:170
作者
SHORTLIFFE, EH [1 ]
BUCHANAN, BG [1 ]
FEIGENBAUM, EA [1 ]
机构
[1] STANFORD UNIV, DEPT COMP SCI, STANFORD, CA 94305 USA
关键词
D O I
10.1109/PROC.1979.11436
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Computer-based models of medical decision making account for a large portion of clinical computing efforts. This article reviews representative examples from each of several major medical computing paradigms. These include 1) clinical algorithms, 2) clinical databanks that include analytic functions, 3) mathematical models of physical processes, 4) pattern recognition, 5) Bayesian statistics, 6) decision analysis, and 7) symbolic reasoning or artificial intelligence. Because the techniques used in the various systems cannot be examined exhaustively, the case studies in each category are used as a basis for studying general strengths and limitations. It is noted that no one method is best for all applications. However, emphasis is given to the limitations of early work that have made artificial intelligence techniques and knowledge engineering research particularly attractive. We stress that considerable basic research in medical computing remains to be done and that powerful new approaches may lie in the melding of two or more established techniques. © 1979 IEEE.
引用
收藏
页码:1207 / 1224
页数:18
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