支持医疗诊断软件系统的贝叶斯知识库的研究评估的通用外壳

Lee Shapiro, D. Stetson
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引用次数: 3

摘要

人工智能专家系统中常用的推理机和知识库分开识别的原理,已经在一个C程序中实现,该程序利用了易于用于研究和临床应用的贝叶斯推理机。给定一组医疗条件的输入特征的相对权重知识库文件,用户可以交互式地或以两种简化模式中的任何一种输入单个病例的特征。病例可以保存在文件中或从文件中检索,并且可以随时在屏幕上显示从知识库计算出的疾病概率。最后,批处理模式允许快速处理大量案例,这些案例的特征包含在单个磁盘文件中。将每种情况的诊断概率写入集合输出文件。这个贝叶斯外壳允许快速评估贝叶斯知识库,以支持知识库和程序开发。它可以嵌入到其他程序中,利用贝叶斯定理来评估任何数据体,无论是临床数据还是其他数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A general purpose shell for research assessment of Bayesian knowledge bases supporting medical diagnostic software systems
The principle of separately identifying an inference engine and a knowledge base, commonly used in AI expert systems, has been realized in a C program that utilizes a Bayesian inference engine easily used in research and clinical applications. Given a knowledge base file of relative weights for the input features of a group of medical conditions, a user can enter features of individual cases interactively or in either of two streamlined modes. A case can be saved in or retrieved from a file, and the disease probabilities calculated from the knowledge base can be displayed on the screen at any time. Finally, a batch mode permits rapid processing of large numbers of cases whose features are contained in a single disk file. The diagnostic probabilities for each case are written to a collection output file. This Bayesian shell permits rapid evaluation of Bayesian knowledge bases in support of knowledge base and program development. It can be embedded in other programs that utilize Bayes' theorem to evaluate any body of data, clinical or otherwise.<>
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