Knowledge discovery in clinical databases and evaluation of discovered knowledge in outpatient clinic
Knowledge discovery in clinical databases and evaluation of discovered knowledge in outpatient clinic
复制标题
临床数据库中的知识发现以及门诊中发现的知识的评估
DOI：
10.1016/s0020-0255(99)00065-1
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发表时间：
2000
期刊：
影响因子：
--
通讯作者：
S. Tsumoto
中科院分区：
文献类型：
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作者：
S. Tsumoto
为了从数据库中自动发现知识，提出了规则归纳方法。然而，传统的方法并不集中在实施的诱导结果到一个专家系统。在本文中，作者不仅关注规则归纳，而且还关注其评估，并提出了一个系统的方法，从前者到后者如下。首先，介绍了一个基于粗糙集和面向属性泛化的规则归纳系统，并将其应用于先天畸形数据库中，提取诊断规则。然后，通过使用的诱导知识，一个专家系统，使先天性疾病的鉴别诊断。最后，该专家系统在门诊进行了评估，结果表明，该系统不仅表现出以及医疗专家，但也是非常有用的指导医疗居民。
Rule induction methods have been proposed in order to discover knowledge automatically from databases. However, conventional approaches do not focus on the implementation of induced results into an expert system. In this paper, the author focuses not only on rule induction but also on its evaluation and presents a systematic approach from the former to the latter as follows. First, a rule induction system based on rough sets and attribute-oriented generalization is introduced and was applied to a database of congenital malformation to extract diagnostic rules. Then, by the use of the induced knowledge, an expert system which makes a differential diagnosis on congenital disorders is developed. Finally, this expert system was evaluated in an outpatient clinic, the results of which show not only that the system performs as well as a medical expert, but also that the system is very useful for instruction to medical residents.