Early prediction of hemodialysis complications employing ensemble techniques.

ABSTRACT:

Background and objectives

Hemodialysis complications remain a critical threat among dialysis patients. They result in sudden termination of the session which impacts the efficiency of dialysis. As intra-dialytic complications are the result of the interplay of multiple factors, artificial intelligence can aid in their early prediction. This research aims to compare different machine learning tools for the early prediction of the most frequent hemodialysis complications with high performance, using the fewest predictors for easier practical implementation.

Methods

Fifty different variables were recorded during 6000 hemodialysis sessions performed in a regional dialysis unit in Egypt. The filter technique was used to extract the most relevant features. Then, five individual cl

SUBMITTER: Othman M 

PROVIDER: S-EPMC9552449 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature