Development and validation of prediction models for hypertension risks: A cross-sectional study based on 4,287,407 participants

OBJECTIVE: To develop an optimal screening model to identify the individuals with a high risk of hypertension in China by comparing tree-based machine learning models, such as classification and regression tree, random forest, adaboost with a decision tree, extreme gradient boosting decision tree, a...

Descripción completa

Detalles Bibliográficos
Autores principales: Ji, Weidong, Zhang, Yushan, Cheng, Yinlin, Wang, Yushan, Zhou, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Cardiovascular Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548597/
https://www.ncbi.nlm.nih.gov/pubmed/36225955
http://dx.doi.org/10.3389/fcvm.2022.928948

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548597/
https://www.ncbi.nlm.nih.gov/pubmed/36225955
http://dx.doi.org/10.3389/fcvm.2022.928948

Ejemplares similares