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[测试一个用于高血压的专家系统]

[Testing an expert system for hypertension].

作者信息

Jeunemaitre X, Degoulet P, Morice V, Chatellier G, Devries C, Plouin P F, Boisvieux J F, Ménard J

出版信息

Arch Mal Coeur Vaiss. 1986 Jun;79(6):808-12.

PMID:3099696
Abstract

An Expert System (ES) has been connected to a database management system for the management and follow-up of hypertensive patients. The patient data base, called Artemis, contains approximately 18,000 medical records. About 90% of the initial informations used by the ES is contained in the medical records of the Artemis data base. The knowledge base consists of 870 rules. A first group of rules allows the description of knowledge structures (hierachies, graphs and mutual exclusions). The second group consists of production rules which describe the dynamic reasoning of the expert. The inference engine uses a combination of forward and backward chaining. The ES produce diagnostic hypotheses (possible causes of hypertension) and therapeutic suggestions before and after requiring additional information (patient supplementary interrogation, biological or radiological investigations). The evaluation of the diagnostic performance of the ES was made on 40 confirmed cases of secondary hypertension (SH) and 40 cases of essential hypertension (EH). The initial initial diagnosis, just after the forward chaining step, was correct in 17 cases of SH and 32 cases of EH. The final diagnosis proposed after several steps of forward and backward chaining was correct in 37 cases (92%) of SH and 36 (90%) of EH. Averages of 5 (EH) and 8 (SH) questions were formulated by the ES to reach the final diagnosis. The integration of the ES to the database is expected to facilitate the validation of the knowledge base and to enhance its overall acceptability. Whether or not such an integration will be useful and accepted as a complementary tool by physicians remains however an open question.

摘要

一个专家系统(ES)已连接到数据库管理系统,用于高血压患者的管理和随访。名为阿尔忒弥斯(Artemis)的患者数据库包含约18,000份医疗记录。专家系统使用的初始信息中约90%包含在阿尔忒弥斯数据库的医疗记录中。知识库由870条规则组成。第一组规则用于描述知识结构(层次结构、图表和互斥关系)。第二组由描述专家动态推理的产生式规则组成。推理引擎结合了正向和反向链推理。在要求提供额外信息(患者补充询问、生物学或放射学检查)之前和之后,专家系统会生成诊断假设(高血压的可能病因)和治疗建议。对40例确诊的继发性高血压(SH)病例和40例原发性高血压(EH)病例进行了专家系统诊断性能评估。在正向链推理步骤之后的初始诊断中,17例SH病例和32例EH病例诊断正确。经过几步正向和反向链推理后提出的最终诊断,在37例(92%)SH病例和36例(90%)EH病例中正确。专家系统为得出最终诊断平均提出了5个(EH)和8个(SH)问题。专家系统与数据库的整合有望促进知识库的验证并提高其整体可接受性。然而,这样的整合是否会有用并被医生接受为一种辅助工具仍是一个悬而未决的问题。

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