Using Bayesian networks with Max-Min Hill-Climbing algorithm to detect factors related to multimorbidity.

ABSTRACT:

Objectives

Multimorbidity (MMD) is a medical condition that is linked with high prevalence and closely related to many adverse health outcomes and expensive medical costs. The present study aimed to construct Bayesian networks (BNs) with Max-Min Hill-Climbing algorithm (MMHC) algorithm to explore the network relationship between MMD and its related factors. We also aimed to compare the performance of BNs with traditional multivariate logistic regression model.

Methods

The data was downloaded from the Online Open Database of CHARLS 2018, a population-based longitudinal survey. In this study, we included 10 variables from data on demographic background, health status and functioning, and lifestyle. Missing value imputation was first performed using Random Forest. Afterward, th

SUBMITTER: Song W 

PROVIDER: S-EPMC9468216 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature