Intelligent Clinical Decision Support Systems Based on SNOMED CT

被引：6
|
作者：
Ciolko, Ewelina [1 ]
Lu, Fletcher [1 ]
Joshi, Amardeep [1 ]
机构：
[1] Univ Ontario, Inst Technol, Fac Hlth Sci, Oshawa, ON, Canada
来源：
2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2010年
关键词：
D O I：
10.1109/IEMBS.2010.5625982
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
The decision support systems that have been developed to assist physicians in the diagnostic process often are based on static data which may be out of date. We present a comprehensive analysis of artificial intelligent methods which could be applied to documents encoded by SNOMED CT. By mining information directly from SNOMED CT encoded documents, a decision support system could contain timely updated diagnostic information, which is of significant value in fast changing situations such as minimally understood emerging diseases and epidemics. Through a high level comparison of many AI methods it is found that a TANBayesian method could be the most suitable to apply to SNOMED CT data.
引用
收藏
页码：6781 / 6784
页数：4
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