Identification of common mechanisms and biomarkers of atrial fibrillation and heart failure based on machine learning.
Zhijun ZhangJianying DingXiaolong MiYuanyuan LinXinjian LiJun LianJinwen LiuLijuan QuBingye ZhaoXuewen LiPublished in: ESC heart failure (2024)
We identified four biological markers that are highly correlated with AF and HF, namely, GLUL, NCF2, S100A12, and SRGN. Our findings provide theoretical basis for the clinical diagnosis and treatment of AF and HF.
Keyphrases
- atrial fibrillation
- heart failure
- acute heart failure
- machine learning
- oral anticoagulants
- catheter ablation
- left atrial
- left atrial appendage
- direct oral anticoagulants
- percutaneous coronary intervention
- left ventricular
- cardiac resynchronization therapy
- bioinformatics analysis
- deep learning
- venous thromboembolism
- mitral valve