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《伊利亚特》与上门医疗服务:评估常识知识对医学专家系统诊断准确性的影响。

Iliad and Medical HouseCall: evaluating the impact of common sense knowledge on the diagnostic accuracy of a medical expert system.

作者信息

Bouhaddou O, Lambert J G, Morgan G E

机构信息

Applied Medical Informatics, Salt Lake City, Utah, USA.

出版信息

Proc Annu Symp Comput Appl Med Care. 1995:742-6.

Abstract

Diagnostic expert systems are gaining acceptance among physicians. Recently, a comparative study of the performance of four major commercial diagnostic programs demonstrated that the information they produce contains a certain amount of irrelevancy that the trained physician ignores. Medical HouseCall is a consumer health information expert system based on a medical expert system for physicians, Iliad. To enhance the usefulness of Medical HouseCall to health care consumers, we are interested in significantly reducing the amount of irrelevancy contained in the diagnostic differential list. Testing with over 470 'textbook' cases revealed that a large part of the irrelevancy can be eliminated by adding universal and medical 'common sense' knowledge. Using four performance measures, we compared, on a subset of cases, the differential lists from two versions of the program: the refined knowledge base (1995) and an older version (1994) 'pre-common sense'. The results suggest that the performance of a diagnostic expert system can be significantly improved with the addition of common sense knowledge.

摘要

诊断专家系统正在逐渐被医生们所接受。最近,一项对四个主要商业诊断程序性能的比较研究表明,它们生成的信息包含一定量的无关内容,而训练有素的医生会忽略这些内容。“医疗上门服务”是一个基于面向医生的医学专家系统“Iliad”的消费者健康信息专家系统。为了提高“医疗上门服务”对医疗保健消费者的实用性,我们有兴趣大幅减少诊断鉴别列表中包含的无关内容量。对470多个“教科书式”病例的测试表明,通过添加通用和医学“常识”知识,可以消除很大一部分无关内容。我们使用四种性能指标,在一部分病例上比较了该程序两个版本的鉴别列表:改进后的知识库(1995年)和旧版本(1994年)“常识前”版本。结果表明,添加常识知识可以显著提高诊断专家系统的性能。

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