Utilizing machine learning algorithms for the prediction of carotid artery plaques in a Chinese population.

ABSTRACT: Background: Ischemic stroke is a significant global health issue, imposing substantial social and economic burdens. Carotid artery plaques (CAP) serve as an important risk factor for stroke, and early screening can effectively reduce stroke incidence. However, China lacks nationwide data on carotid artery plaques. Machine learning (ML) can offer an economically efficient screening method. This study aimed to develop ML models using routine health examinations and blood markers to predict the occurrence of carotid artery plaques. Methods: This study included data from 5,211 participants aged 18-70, encompassing health check-ups and biochemical indicators. Among them, 1,164 participants were diagnosed with carotid artery plaques through carotid ultrasound. We constructed six ML

SUBMITTER: Weng S 

PROVIDER: S-EPMC10657816 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature