Temporal rule induction for clinical outcome analysis Online publication date: Tue, 05-Jul-2005
by Xiaohua Hu, Il-Yeol Song, Hyoil Han, Illhoi Yoo, Ann A. Prestrud, Murray F. Brennan, Ari D. Brooks
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 1, No. 1, 2005
Abstract: 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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