Author Credentials

Zeid Khitan MD Alexis D. Jacob MD Courtney Balentine MD Adam N. Jacob BS Juan R. Sanabria MD Joseph I. Shapiro MD


machine learning, end stage renal disease, mortality, hemodialysis


Health and Medical Administration | Nephrology


We examined machine learning methods to predict death within six months using data derived from the United States Renal Data System (USRDS). We specifically evaluated a generalized linear model, a support vector machine, a decision tree and a random forest evaluated within the context of K-10 fold validation using the CARET package available within the open source architecture R program. We compared these models with the feed forward neural network strategy that we previously reported on with this data set.