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Temporal rule induction for clinical outcome analysis
Journal article   Peer reviewed

Temporal rule induction for clinical outcome analysis

Xiaohua Hu, Il-Yeol Song, Hyoil Han, Illhoi Yoo, Ann Prestrud, Murray Brennan and Ari Brooks
International journal of business intelligence and data mining, v 1(1)
01 Jan 2005
DOI: https://doi.org/10.1504/IJBIDM.2005.007322

Abstract

cancer epidemiologic research data mining temporal rules cancer patients association rules clinical outcome analysis clinical data assessment database design healthcare data temporal rule induction survival analysis patient information statistical analysis
Clinical outcomes analysis normally covers a particular time period. The sample under study is constantly changing as patients are censored, leave the study or die. In this paper, we present a novel data mining approach to mine temporal rules that reflect characteristics of outcomes analysis. We apply our temporal rule induction algorithm to a set of cancer patients, clinical records that were prospectively collected for 20 years. We analyse clinical data not only based on the static event, such as local recurrence for survival analysis, but also based on the temporal event with censored data for each time unit. The rules extracted from our temporal rule induction algorithm are compared to results from statistical analysis. The importance of this paper is that this novel temporal rule induction algorithm provides valuable insights for clinical data assessment and complements traditional statistical analysis.

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17 citations in Scopus

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