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

Machine Learning (2992) Clinical Information and Decision Making (3455) mHealth in a Clinical Setting (1081) Decision Support for Health Professionals (2074) Hypertension Prevention and Treatment (339) Cardiac Risk and Cardiac Risk Calculators (157)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/74117, first published .
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Interpretable Machine Learning Model for Pulmonary Hypertension Risk Prediction: Retrospective Cohort Study

Interpretable Machine Learning Model for Pulmonary Hypertension Risk Prediction: Retrospective Cohort Study

Authors of this article:

Hongxia Jiang1 Author Orcid Image ;   Han Gao1 Author Orcid Image ;   Dexin Wang2 Author Orcid Image ;   Qingli Zeng1 Author Orcid Image ;   Xiaojun Hao1 Author Orcid Image ;   Zhenshun Cheng1, 3, 4 Author Orcid Image
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Journals

  1. Taigonyrov A, Rai H, Jamwal P, Pal A, Razaque A. A Systematic Review of AI for Pulmonary Hypertension Detection: Performance, Gaps, and the Critical Need for Federated Learning. Archives of Computational Methods in Engineering 2026 View
  2. Tan X, Fowler J, Li M, Guha A. Artificial intelligence for right ventricular assessment: current evidence and future directions. Current Opinion in Cardiology 2026 View