This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1935) Machine Learning (2095) Cardiac Surgery (20) Heart Valve Disease Research (6) Cardiac Risk and Cardiac Risk Calculators (107) Cardiology (228)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70587, first published .
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

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

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

Authors of this article:

Jun Wang1, 2, 3 Author Orcid Image ;   Jiajun Zhu4 Author Orcid Image ;   Hui Li1 Author Orcid Image ;   Shili Wu1, 5 Author Orcid Image ;   Siyang Li6 Author Orcid Image ;   Zhuoya Yao1 Author Orcid Image ;   Tongjian Zhu6 Author Orcid Image ;   Bi Tang1, 2, 3 Author Orcid Image ;   Shengxing Tang7 Author Orcid Image ;   Jinjun Liu1, 2, 3 Author Orcid Image
Article Authors Cited by (5) Tweetations Metrics

Journals

  1. Zhu J, Wang Y, Duan S, Liu C, Yin W, Yang Y, Zhu T, Wang J. Multivariable data-driven framework of predictive, preventive, and personalized medicine for long-term atrial fibrillation risk in patients with new-onset obstructive sleep apnea. EPMA Journal 2025;16(4):761 View
  2. Potoupni V, Samaras A, Papadopoulos C, Boulmpou A, Moysiadis T, Zormpas G, Tzikas A, Fragakis N, Giannakoulas G, Vassilikos V. Machine-Learning-Driven Phenotyping in Heart Failure with Preserved Ejection Fraction: Current Approaches and Future Directions. Medicina 2025;61(11):1937 View
  3. Duan S, Wang Y, Yang X, Xu Y, Wang J. Explainable machine learning‐driven predictive modelling of incident cognitive impairment in individuals with early‐stage cardiovascular–kidney–metabolic syndrome: Insights from a longitudinal CHARLS cohort study. Diabetes, Obesity and Metabolism 2025 View
  4. Wang Y, Wang Y, Luan Y, Hao M, Yin W, Wu B, Zhu T, Zhu J, Zhou B, Tang L, Wang J, Wu J. Multimodal Data–Driven Explainable Prognostic Model for Major Adverse Cardiovascular Events Prediction in Patients With Unstable Angina and Heart Failure With Preserved Ejection Fraction: Multicenter, Cross-Regional Cohort Study. Journal of Medical Internet Research 2025;27:e78402 View

Conference Proceedings

  1. Olariu M, Iftene A. 2025 International Conference on INnovations in Intelligent SysTems and Applications (INISTA). Analysis of Current Applications of Artificial Intelligence in Cardiology Diagnosis with Focus on Explainable AI, Holter Monitoring and Blood Biomarkers View