文章基本信息

标题：Development of EMR Analysis Support Tool based on TETDM and Its Evaluation through Actual EMR Analysis
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作者：Yasufumi Takama ; Muneo Kushima ; Wataru Sunayama 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2015
卷号：30
期号：1
页码：372-382
DOI：10.1527/tjsai.30.372
出版社：The Japanese Society for Artificial Intelligence
摘要：This paper proposes an analysis support tool for EMR (electronic medical record), based on which examines its applicability to EMR analysis task in a hospital. As the spread of EMR into hospitals, the demand for analyzing EMR for improving quality of medical care as well as for contributing to hospital management is increasing. Although application of data mining techniques is promising, it has not been so popular today. The proposed tool consists of two sub-tools: a tool for analyzing EMR with visualization, and that for adding technical terms to a dictionary used by a morphological analyzer. Those are developed on TETDM (Total Environment for Text Data Mining), which makes it possible for users to use multiple tools through unified interface. In order to examine the applicability of the proposed tools and TETDM to EMR analysis in a hospital, doctors and nurses in a hospital used the tool for analyzing actual EMR. The experimental result shows that they can analyze the difference between EMR written by novice nurses and veteran. It is also shown adding technical terms extracted from EMR is useful for improving the quality of text processing as well as for reducing ambiguity of terms.
关键词：text mining ; EMR ; TETDM ; exploratory data analysis