An application of the Bayesian network model based on the EN-ESL-GA algorithm: Exploring the predictors of heart disease in middle-aged and elderly people in China.
Technol Health Care
; 2024 Jun 20.
Article
em En
| MEDLINE
| ID: mdl-38968062
ABSTRACT
BACKGROUND:
The morbidity and mortality of heart disease are increasing in middle-aged and elderly people in China. It is necessary to explore relationships and interactive associations between heart disease and its risk factors in order to prevent heart disease.OBJECTIVE:
To establish a Bayesian network model of heart disease and its influencing factors in middle-aged and elderly people in China, and explore the applicability of the elite-based structure learner using genetic algorithm based on ensemble learning (EN-ESL-GA) algorithm in etiology analysis and disease prediction.METHODS:
Based on the 2013 national tracking survey data from China Health and Retirement Longitudinal Study (CHARLS) database, EN-ESL-GA algorithm was used to learn the Bayesian network structure. Then we input the data and the learned network structure into the Netica software for parameter learning and inference analysis.RESULTS:
The Bayesian network model based on the EN-ESL-GAalgorithm can effectively excavate the complex network relationships and interactive associations between heart disease and its risk factors in middle-aged and elderly people in China.CONCLUSIONS:
The Bayesian network model based on the EN-ESL-GA algorithm has good applicability and application prospect in the prediction of diseases prevalence risk.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Technol Health Care
Ano de publicação:
2024
Tipo de documento:
Article