Deep Learning in Prediction of Late Major Bleeding After Transcatheter Aortic Valve Replacement.
Yuheng JiaGaden LuosangYi Ming LiJianyong WangPengyu LiTianyuan XiongYijian LiYanbiao LiaoZhengang ZhaoYong PengYuan FengWeili JiangWenjian LiXinpei ZhangZhang YiMao ChenPublished in: Clinical epidemiology (2022)
Deep learning is a feasible way to build prediction models concerning TAVR prognosis. A dedicated bleeding risk prediction model was developed for TAVR patients to facilitate well-informed clinical decisions.
Keyphrases
- transcatheter aortic valve replacement
- deep learning
- aortic stenosis
- aortic valve
- ejection fraction
- end stage renal disease
- newly diagnosed
- atrial fibrillation
- chronic kidney disease
- peritoneal dialysis
- prognostic factors
- artificial intelligence
- convolutional neural network
- patient reported outcomes
- patient reported