Methods and Tools for Mining Multivariate Temporal Data in Clinical and Biomedical Applications

被引：6

作者：

Bellazzi, Riccardo ^{[1
]}

Sacchi, Lucia ^{[1
]}

Concaro, Stefano ^{[1
]}

机构：

[1] Univ Pavia, Dipartimento Informat & Sistemist, I-27100 Pavia, Italy

来源：

2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20 | 2009年

关键词：

D O I：

10.1109/IEMBS.2009.5333788

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Temporal data mining is becoming an important tool for health care providers and decision makers. The capability of handling and analyzing complex multivariate data may allow to extract useful information coming from the day-by-day activity of health care organizations as well as from patients monitoring. In this paper we review the main approaches presented in the literature to mine biomedical time sequences and we present a novel approach able to deal with "point-like" and "interval-like" events. The methods is described and the results obtained on two clinical data sets are shown.

引用

页码：5629 / 5632

页数：4

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