Predicting mortality in hemodialysis patients using machine learning analysis.

ABSTRACT:

Background

Besides the classic logistic regression analysis, non-parametric methods based on machine learning techniques such as random forest are presently used to generate predictive models. The aim of this study was to evaluate random forest mortality prediction models in haemodialysis patients.

Methods

Data were acquired from incident haemodialysis patients between 1995 and 2015. Prediction of mortality at 6 months, 1 year and 2 years of haemodialysis was calculated using random forest and the accuracy was compared with logistic regression. Baseline data were constructed with the information obtained during the initial period of regular haemodialysis. Aiming to increase accuracy concerning baseline information of each patient, the period of time used to collect data was

SUBMITTER: Garcia-Montemayor V 

PROVIDER: S-EPMC8247746 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature