CAUSAL PROBABILISTIC NETWORK MODELING - AN ILLUSTRATION OF ITS ROLE IN THE MANAGEMENT OF CHRONIC DISEASES

被引:25
作者
HOVORKA, R
ANDREASSEN, S
BENN, JJ
OLESEN, KG
CARSON, ER
机构
[1] UMDS,ST THOMAS HOSP,DEPT MED,LONDON SE1 7EH,ENGLAND
[2] AALBORG UNIV,DEPT MED INFORMAT & IMAGE ANAL,DK-9220 AALBORG E,DENMARK
关键词
D O I
10.1147/sj.314.0635
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper describes the role of the novel technique of causal probabilistic network (CPN) modeling as an approach to tackling control system problems typified by that of the administration of treatment to the patient suffering from a chronic disease such as diabetes. Three roles of a CPN are discussed. First, since diabetes arises as a consequence of impaired control of carbohydrate metabolism, the ability of a CPN to represent the uncertainty of a physiologically-based model is described. Second, its ability to make robust estimates of the parameters of the metabolic model is presented, and finally, in conjunction with decision theory approaches, its ability to compare alternative therapies and advise on insulin therapy for patients with insulin-dependent diabetes mellitus is illustrated.
引用
收藏
页码:635 / 648
页数:14
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