Mortality prediction system for heart failure with orthogonal relief and dynamic radius means

International Journal of Medical Informatics
Zhe WangJu Gao

Abstract

This paper constructs a mortality prediction system based on a real-world dataset. This mortality prediction system aims to predict mortality in heart failure (HF) patients. Effective mortality prediction can improve resources allocation and clinical outcomes, avoiding inappropriate overtreatment of low-mortality patients and discharging of high-mortality patients. This system covers three mortality prediction targets: prediction of in-hospital mortality, prediction of 30-day mortality and prediction of 1-year mortality. HF data are collected from the Shanghai Shuguang hospital. 10,203 in-patients records are extracted from encounters occurring between March 2009 and April 2016. The records involve 4682 patients, including 539 death cases. A feature selection method called Orthogonal Relief (OR) algorithm is first used to reduce the dimensionality. Then, a classification algorithm named Dynamic Radius Means (DRM) is proposed to predict the mortality in HF patients. The comparative experimental results demonstrate that mortality prediction system achieves high performance in all targets by DRM. It is noteworthy that the performance of in-hospital mortality prediction achieves 87.3% in AUC (35.07% improvement). Moreover, the AUC ...Continue Reading

Citations

Nov 5, 2019·International Journal for Numerical Methods in Biomedical Engineering·Zhe WangDongdong Li
Mar 9, 2019·Biomedical Engineering Online·Daniel NogueiraMaria Teresa Restivo
Aug 29, 2020·Journal of Biomedical Informatics·Renji P CherianSunder Venkitachalam

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