SrasV1, Main, Exploration, bibRecord, 001851

Survival Association Rule Mining Towards Type 2 Diabetes Risk Assessment

Identifieur interne : 001851 ( Main/Exploration ); précédent : 001850; suivant : 001852

Survival Association Rule Mining Towards Type 2 Diabetes Risk Assessment

Auteurs : Gyorgy J. Simon [États-Unis] ; John Schrom [États-Unis] ; M. Regina Castro [États-Unis] ; Peter W. Li [États-Unis] ; Pedro J. Caraballo [États-Unis]

Source :

AMIA Annual Symposium Proceedings [ 1942-597X ] ; 2013.

RBID : PMC:3900145

Abstract

Type-2 Diabetes Mellitus is a growing epidemic that often leads to severe complications. Effective preventive measures exist and identifying patients at high risk of diabetes is a major health-care need.

The use of association rule mining (ARM) is advantageous, as it was specifically developed to identify associations between risk factors in an interpretable form. Unfortunately, traditional ARM is not directly applicable to survival outcomes and it lacks the ability to compensate for confounders and to incorporate dosage effects. In this work, we propose Survival Association Rule (SAR) Mining, which addresses these shortcomings.

We demonstrate on a real diabetes data set that SARs are naturally more interpretable than the traditional association rules, and predictive models built on top of these rules are very competitive relative to state of the art survival models and substantially outperform the most widely used diabetes index, the Framingham score.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900145

PubMed: 24551408
PubMed Central: 3900145

Affiliations:

Le document en format XML

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<p><italic>The use of association rule mining (ARM) is advantageous, as it was specifically developed to identify associations between risk factors in an interpretable form. Unfortunately, traditional ARM is not directly applicable to survival outcomes and it lacks the ability to compensate for confounders and to incorporate dosage effects. In this work, we propose Survival Association Rule (SAR) Mining, which addresses these shortcomings</italic>
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Survival Association Rule Mining Towards Type 2 Diabetes Risk Assessment

Survival Association Rule Mining Towards Type 2 Diabetes Risk Assessment

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