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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Frontiers in endocrinology (Lausanne) Ročník 15; s. 1390352
Hlavní autoři:	Zhang, Xiaoshuai, Tang, Chuanping, Wang, Shuohuan, Liu, Wei, Yang, Wangxuan, Wang, Di, Wang, Qinghuan, Tang, Fang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland Frontiers Media S.A 23.07.2024
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!