Predicting Outcomes of Hospitalization for Heart Failure Using Logistic Regression and Knowledge Discovery Methods

Abstract

The purpose of this study is to determine the best prediction of heart failure outcomes, resulting from two methods -- standard epidemiologic analysis with logistic regression and knowledge discovery with supervised learning/data mining. Heart failure was chosen for this study as it exhibits higher prevalence and cost of treatment than most other… (More)

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Cite this paper

@article{Phillips2005PredictingOO, title={Predicting Outcomes of Hospitalization for Heart Failure Using Logistic Regression and Knowledge Discovery Methods}, author={Kirk T. Phillips and William Nick Street}, journal={AMIA ... Annual Symposium proceedings. AMIA Symposium}, year={2005}, pages={1080} }