Semantic Data Types in Machine Learning from Healthcare Data

被引：3

作者：

Wojtusiak, Janusz ^{[1
]}

机构：

[1] George Mason Univ, Ctr Discovery Sci & Hlth Informat, Machine Learning & Inference Lab, Fairfax, VA 22030 USA

来源：

2012 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2012), VOL 1 | 2012年

关键词：

semantic data types; UMLS; machine learning; healthcare;

D O I：

10.1109/ICMLA.2012.41

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Healthcare is particularly rich in semantic information and background knowledge describing data. This paper discusses a number of semantic data types that can be found in healthcare data, presents how the semantics can be extracted from existing sources including the Unified Medical Language System (UMLS), discusses how the semantics can be used in both supervised and unsupervised learning, and presents an example rule learning system that implements several of these types. Results from three example applications in the healthcare domain are used to further exemplify semantic data types.

引用

页码：197 / 202

页数：6

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