Predictors of rapid eye movement sleep behavior disorder in patients with Parkinson's disease based on random forest and decision tree.

ABSTRACT:

Background and objectives

Sleep disorders related to Parkinson's disease (PD) have recently attracted increasing attention, but there are few clinical reports on the correlation of Parkinson's disease patients with rapid eye movement (REM) sleep behavior disorder (RBD). Therefore, this study conducted a cognitive function examination for Parkinson's disease patients and discussed the application effect of three algorithms in the screening of influencing factors and risk prediction effects.

Methods

Three algorithms (logistic regression, machine learning-based regression trees and random forest) were used to establish a prediction model for PD-RBD patients, and the application effects of the three algorithms in the screening of influencing factors and the risk prediction of PD

SUBMITTER: Chong-Wen W 

PROVIDER: S-EPMC9202951 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature