A Machine Learning Model Based on Genetic and Traditional Cardiovascular Risk Factors to Predict Premature Coronary Artery Disease-Reference-Cited by-同舟云学术

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A Machine Learning Model Based on Genetic and Traditional Cardiovascular Risk Factors to Predict Premature Coronary Artery Disease

Published:2022-07-04 Issue:7 Volume:27 Page:211
ISSN:2768-6701
Container-title:Frontiers in Bioscience-Landmark
language:en
Short-container-title:Front. Biosci. (Landmark Ed)

Author:

Liu Benrong,Fang Lei,Xiong Yujuan,Du Qiqi,Xiang Yang,Chen Xiaohui,Tian Chao-Wei,Liu Shi-Ming

Publisher

IMR Press

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Development and validation of a nomogram for premature coronary artery disease patients in Guangzhou;IJC Heart & Vasculature;2024-08

2. Decreased plasma miR-140-3p is associated with coronary artery disease;Heliyon;2024-03

3. Artificial intelligence in preventive cardiology;Progress in Cardiovascular Diseases;2024-03

4. Genetics-based risk scores for prediction of premature coronary artery disease;Indian Heart Journal;2023-09

5. Use of machine learning to identify risk factors for coronary artery disease;PLOS ONE;2023-04-14

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