Machine learning-based prediction of carotid intima–media thickness progression: a three-year prospective cohort study

Machine learning-based prediction of carotid intima–media thickness progression: a three-year prospective cohort study

BackgroundEarly detection of subclinical atherosclerosis progression is crucial for preventing atherosclerotic cardiovascular disease (ASCVD). Carotid intima–media thickness (CIMT) is a recognized surrogate marker for atherosclerosis, but accurate prediction of its progression remains challenging. T...

Full description

Saved in:
Bibliographic Details
Main Authors: An Zhou, Kui Chen, Yonghui Wei, Qu Ye, Yuanming Xiao, Rong Shi, Jiangang Wang, Wei-Dong Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Medicine
Subjects:
carotid intima–media thickness (CIMT)
machine learning
atherosclerosis progression
risk prediction
cardiovascular prevention
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1593662/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items