Middleton B, Shwe M A, Heckerman D E, Henrion M, Horvitz E J, Lehmann H P, Cooper G F
Section on Medical Informatics, Stanford University, CA.
Methods Inf Med. 1991 Oct;30(4):256-67.
We have developed a probabilistic reformulation of the Quick Medical Reference (QMR) system. In Part I of this two-part series, we described a two-level, multiply connected belief-network representation of the QMR knowledge base and a simulation algorithm to perform probabilistic inference on the reformulated knowledge base. In Part II of this series, we report on an evaluation of the probabilistic QMR, in which we compare the performance of QMR to that of our probabilistic system on cases abstracted from continuing medical education materials from Scientific American Medicine. In addition, we analyze empirically several components of the probabilistic model and simulation algorithm.
我们已经开发出了一种对快速医学参考（QMR）系统的概率性重新表述。在这个两部分系列的第一部分中，我们描述了QMR知识库的一种两级、多重连接的信念网络表示以及一种对重新表述后的知识库进行概率推理的模拟算法。在本系列的第二部分中，我们报告了对概率性QMR的评估情况，其中我们将QMR的性能与我们的概率性系统在从《科学美国人医学》的继续医学教育材料中提取的案例上的性能进行了比较。此外，我们还对概率模型和模拟算法的几个组成部分进行了实证分析。
