Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease.
Yaozhong LiuFan BaiZhenwei TangNa LiuQi Ming LiuPublished in: BMC cardiovascular disorders (2021)
Taken together, our present work might provide novel insights into the molecular mechanism and provide some promising diagnostic and therapeutic targets of AF.
Keyphrases
- atrial fibrillation
- machine learning
- oral anticoagulants
- catheter ablation
- left atrial
- left atrial appendage
- direct oral anticoagulants
- heart failure
- artificial intelligence
- deep learning
- big data
- single cell
- percutaneous coronary intervention
- pulmonary hypertension
- genome wide
- rna seq
- bioinformatics analysis
- label free
- coronary artery disease
- dna methylation
- left ventricular
- mitral valve
- transcription factor