An end stage kidney disease predictor based on an artificial neural networks ensemble

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摘要

IgA Nephropathy (IgAN) is a worldwide disease that affects kidneys in human beings and leads to end-stage kidney disease (ESKD) thus requiring renal replacement therapy with dialysis or kidney transplantation. The need for new tools able to help clinicians in predicting ESKD risk for IgAN patients is highly recognized in the medical field. In this paper we present a software tool that exploits the power of artificial neural networks to classify patients’ health status potentially leading to ESKD. The classifier leverages the results returned by an ensemble of 10 networks trained by using data collected in a period of 38 years at University of Bari. The developed tool has been made available both as an online Web application and as an Android mobile app. Noteworthy to its clinical usefulness is that its development is based on the largest available cohort worldwide.

论文关键词:Clinical decision support system (CDSS),Neural networks ensemble,End stage kidney disease,Machine learning

论文评审过程:Available online 30 January 2013.

论文官网地址:https://doi.org/10.1016/j.eswa.2013.01.046