Comparing the performance of machine learning and conventional models for predicting atherosclerotic cardiovascular disease in a general Chinese population

Comparing the performance of machine learning and conventional models for predicting atherosclerotic cardiovascular disease in a general Chinese population

Abstract Background Accurately predicting the risk of atherosclerotic cardiovascular disease (ASCVD) is crucial for implementing individualized prevention strategies and improving patient outcomes. Our objective is to develop machine learning (ML)-based models for predicting ASCVD risk in a prospect...

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Bibliographic Details
Main Authors: Zihao Fan, Zhi Du, Jinrong Fu, Ying Zhou, Pengyu Zhang, Chuning Shi, Yingxian Sun
Format: Article
Language:English
Published: BMC 2023-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Machine learning
Risk Assessment/classification
Electrocardiography
Echocardiography
ASCVD
Online Access:https://doi.org/10.1186/s12911-023-02242-z

Internet

https://doi.org/10.1186/s12911-023-02242-z

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