Predicting Adverse Outcomes in End Stage Renal Disease: Machine Learning Applied to the United States Renal Data System

Predicting Adverse Outcomes in End Stage Renal Disease: Machine Learning Applied to the United States Renal Data System

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 v...

Full description

Bibliographic Details
Main Authors: Zeid Khitan, Alexis D. Jacob, Courtney Balentine, Adam N. Jacob, Juan R. Sanabria, Joseph I. Shapiro
Format: Article
Language:English
Published: Marshall University 2018-10-01
Series:Marshall Journal of Medicine
Subjects:
machine learning
end stage renal disease
mortality
hemodialysis
Online Access:https://mds.marshall.edu/cgi/viewcontent.cgi?article=1179&context=mjm

Internet

https://mds.marshall.edu/cgi/viewcontent.cgi?article=1179&context=mjm

Similar Items