Multimodal Visualization and Explainable Machine Learning–Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction After Transcatheter Aortic Valve Replacement: Multicenter Cohort Study
BackgroundCurrently, there is a paucity of literature addressing personalized risk stratification using multimodal data in patients with symptomatic aortic stenosis and heart failure with preserved ejection fraction (HFpEF) following transcatheter aortic valve replacement (TA...
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| Main Authors: | Jun Wang, Jiajun Zhu, Hui Li, Shili Wu, Siyang Li, Zhuoya Yao, Tongjian Zhu, Bi Tang, Shengxing Tang, Jinjun Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-05-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e70587 |
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