Automated Discovery of Medical Expert System Rules from Clinical Databases Based on Rough Sets
Automated Discovery of Medical Expert System Rules from Clinical Databases Based on Rough Sets
复制标题
DOI：
--
复制
发表时间：
1996-08
期刊：
影响因子：
--
通讯作者：
S. Tsumoto;Hiroshi Tanaka
中科院分区：
文献类型：
--
作者：
S. Tsumoto;Hiroshi Tanaka
知识自动获取是解决专家系统开发中的瓶颈问题的重要研究课题。虽然许多归纳学习方法已经提出了这一目的，大多数的方法只集中在归纳分类规则。然而，医学专家还从临床病例中了解其他对诊断重要的信息。本文介绍了一种规则归纳方法，该方法不仅可以提取分类规则，而且可以提取诊断所需的其他医学知识。该系统进行了评估的临床数据库头痛，其实验结果表明，我们提出的方法正确地归纳出诊断规则和估计的统计措施的规则。
Automated knowledge acquisition is an important research issue to solve the bottleneck problem in developing expert systems. Although many inductive learning methods have been proposed for this purpose, most of the approaches focus only on inducing classification rules. However, medical experts also learn other information important for diagnosis from clinical cases. In this paper, a rule induction method is introduced, which extracts not only classification rules but also other medical knowledge needed for diagnosis. This system is evaluated on a clinical database of headache, whose experimental results show that our proposed method correctly induces diagnostic rules and estimates the statistical measures of rules.