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

Digital Health Reviews (1820) Machine Learning (2225) Clinical Information and Decision Making (2067) Cardiology (238) Cardiovascular Disease Prevention (215)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77339, first published .
Machine Learning in the Prediction of Venous Thromboembolism: Systematic Review and Meta-Analysis

Machine Learning in the Prediction of Venous Thromboembolism: Systematic Review and Meta-Analysis

Machine Learning in the Prediction of Venous Thromboembolism: Systematic Review and Meta-Analysis

Authors of this article:

Ruyi Ma1, 2 Author Orcid Image ;   Weifeng Yu3 Author Orcid Image ;   Jian Tian2 Author Orcid Image ;   Yunyan Tang2 Author Orcid Image ;   Hua Fang2 Author Orcid Image ;   Xin Ming2 Author Orcid Image ;   Hua Liu2 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Journals

  1. Duranteau O, Leon D. Artificial intelligence-driven predictive analytics for postoperative management and recovery in trauma patients. Current Opinion in Anaesthesiology 2026;39(2):154 View
  2. Leung P, Ho P, Lim H. Contemporary Challenges in Venous Thromboembolism: Evolving Populations and Implications for Management and Risk Stratification. Journal of Clinical Medicine 2026;15(4):1509 View
  3. Crisan D, Cut T, Herlo L, Ivanovic N, Herlo A, Alexandrescu L, Sălcudean A, Dumache R. Artificial Intelligence in Venous Thromboembolism Prevention: A Narrative Review of Machine Learning, Deep Learning, and Natural Language Processing. Journal of Cardiovascular Development and Disease 2026;13(3):119 View