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

Artificial Intelligence (4956) Cardiology (285) Machine Learning (3317) #xCardiovascularMedicine (22) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (175)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68872, first published .
Modern MRI scanner with patient table and control panel in a clean medical room.

The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review

The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review

Authors of this article:

Yuchen Ma1 Author Orcid Image ;   Mohan Li1 Author Orcid Image ;   Huiqun Wu1 Author Orcid Image
Article Authors Cited by (7) Tweetations Metrics

Journals

  1. Niazai A, Jamil H, Hameed M, Sheikh S, Nisar M. Artificial intelligence in cardiovascular diagnostics: a systematic review and descriptive analysis of clinical applications and diagnostic performance. BMC Cardiovascular Disorders 2025;25(1) View
  2. Ju L, Guo Y, Guo H, Liu R, Wang Y, Wang S, Ma N, Ren J. Diagnostic Performance of Deep Learning and Radiomics in Extracranial Carotid Plaque Detection: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2026;28:e77092 View
  3. Zhao X, Wang Z, Yang Q, Liu H, Li Y, Ye X. Establishment and validation of an interpretable machine learning-based predictive model for risk of post-PCI in-hospital heart failure in AIHD patients. Frontiers in Cardiovascular Medicine 2026;13 View
  4. Masri S, Sezdi M. Comparative review of coronary CT angiography versus conventional catheter angiography: diagnostic value, clinical outcomes, and underlying technical principles. Expert Review of Medical Devices 2026;23(8):943 View
  5. Lv Y, Sun S, Zhang Y, Niu Q, Li J, Zhong L. Trends and hotspots in artificial intelligence applications for atherosclerosis research: A bibliometric analysis. DIGITAL HEALTH 2026;12 View
  6. Peng Y, Li R, Li H, Zhou J, Liu X, Valente G, de Campos Melo T, Chen S, Gu L. Toward Individualized Atherosclerosis Therapy: Clinical Endotypes, Programmable Therapeutics, and Delivery Constraints. Medicine Bulletin 2026;2(4):388 View
  7. Chunta A, Gilbert C, Labib D, Amakiri A, Feng Y, Alavi Fili A, Chew D, Chow B, Graham M, Garcia J, Bento M, White J, Miller R. A Parsimonious Machine Learning Model for Predicting Invasive Coronary Angiography Referral After Coronary Computed Tomography Angiography: Development and Multicentre External Validation. Journal of Clinical Medicine 2026;15(19):7641 View