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

New Methods (1169) Clinical Information and Decision Making (2037) Machine Learning (2199) Cardiac Disease Management (164) Cardiac Risk and Cardiac Risk Calculators (114) Decision Support for Health Professionals (1612) Cardiology (234)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78402, first published .
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

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

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

Authors of this article:

Yijun Wang1 Author Orcid Image ;   Yaoling Wang1 Author Orcid Image ;   Yujie Luan1 Author Orcid Image ;   Menglei Hao1 Author Orcid Image ;   Wenyuan Yin2 Author Orcid Image ;   Bing Wu3 Author Orcid Image ;   Tongjian Zhu4 Author Orcid Image ;   Jiajun Zhu5 Author Orcid Image ;   Bowen Zhou6 Author Orcid Image ;   Long Tang7 Author Orcid Image ;   Jun Wang8 Author Orcid Image ;   Jinhui Wu1 Author Orcid Image
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Journals

  1. Xu Q, Xu Y, Wang Y, Liu S, Yang Y, Zhao H, Duan S, Wang J. Multiple machine-learning-driven metabolic frameworks for long-term prognostic risk assessment in patients with coexisting hypertension and obstructive sleep apnea:insights from a multicenter cohort study. Frontiers in Physiology 2026;17 View