Add to ORKGWe 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
Background and objective: Chronic Kidney Disease (CKD) is a condition characterized by a progressive...
End stage renal disease (ESRD) condition increases the risk of cardiovascular (CV) morbidity and sud...
Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-lea...
We examined machine learning methods to predict death within six months using data derived from the ...
Background: Understanding factors which predict progression of renal failure is of great interest to...
Background and ObjectivesChronic kidney disease progression to ESKD is associated with a marked incr...
Abstract Introduction End-stage kidney disease (ESKD) is associated with increased morbidity and mor...
© 2018 IEEE. Chronic Kidney Disease is a serious lifelong condition that induced by either kidney pa...
INTRODUCTION: Several factors affect the survival of End Stage Kidney Disease (ESKD) patients on dia...
BackgroundThe first 90 days after dialysis initiation are associated with high morbidity and mortali...
Objectives: Chronic kidney disease (CKD) is one of the main causes of morbidity and mortality worldw...
Aim: To predict end-stage renal disease (ESRD) in patients with type 2 diabetes by using machine-lea...
Chronic kidney disease (CKD) patients have high risks of end-stage kidney disease (ESKD) and pre-ESK...
The main objective of this manuscript is to report on research where we took advantage of those avai...
IntroductionGiven the high mortality rate within the first year of dialysis initiation, an accurate ...
Background and objective: Chronic Kidney Disease (CKD) is a condition characterized by a progressive...
End stage renal disease (ESRD) condition increases the risk of cardiovascular (CV) morbidity and sud...
Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-lea...
We examined machine learning methods to predict death within six months using data derived from the ...
Background: Understanding factors which predict progression of renal failure is of great interest to...
Background and ObjectivesChronic kidney disease progression to ESKD is associated with a marked incr...
Abstract Introduction End-stage kidney disease (ESKD) is associated with increased morbidity and mor...
© 2018 IEEE. Chronic Kidney Disease is a serious lifelong condition that induced by either kidney pa...
INTRODUCTION: Several factors affect the survival of End Stage Kidney Disease (ESKD) patients on dia...
BackgroundThe first 90 days after dialysis initiation are associated with high morbidity and mortali...
Objectives: Chronic kidney disease (CKD) is one of the main causes of morbidity and mortality worldw...
Aim: To predict end-stage renal disease (ESRD) in patients with type 2 diabetes by using machine-lea...
Chronic kidney disease (CKD) patients have high risks of end-stage kidney disease (ESKD) and pre-ESK...
The main objective of this manuscript is to report on research where we took advantage of those avai...
IntroductionGiven the high mortality rate within the first year of dialysis initiation, an accurate ...
Background and objective: Chronic Kidney Disease (CKD) is a condition characterized by a progressive...
End stage renal disease (ESRD) condition increases the risk of cardiovascular (CV) morbidity and sud...
Herein, we aim to assess mortality risk prediction in peritoneal dialysis patients using machine-lea...