A stacking ensemble model for predicting the occurrence of carotid atherosclerosis

Carotid atherosclerosis (CAS) is a significant risk factor for cardio-cerebrovascular events. The objective of this study is to employ stacking ensemble machine learning techniques to enhance the prediction of CAS occurrence, incorporating a wide range of predictors, including endocrine-related mark...

Full description

Saved in:

Bibliographic Details
Published in:	Frontiers in endocrinology (Lausanne) Vol. 15; p. 1390352
Main Authors:	Zhang, Xiaoshuai, Tang, Chuanping, Wang, Shuohuan, Liu, Wei, Yang, Wangxuan, Wang, Di, Wang, Qinghuan, Tang, Fang
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media S.A 23.07.2024
Subjects:	Aged Algorithms Carotid Artery Diseases - epidemiology carotid atherosclerosis Cohort Studies endocrine-related markers Endocrinology Female Humans Machine Learning Male Middle Aged prediction Prognosis Risk Assessment - methods Risk Factors stacking Support Vector Machine carotid atherosclerosis prediction endocrine-related markers machine learning stacking
ISSN:	1664-2392, 1664-2392
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!