Accessibility settings

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

Reviews in Medical Informatics (127) Machine Learning (2306) Cardiac Disease Management (168) Cardiovascular Disease Prevention (221) Artificial Intelligence (2458) Applications of AI (382)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64349, first published .
Man working on laptop at desk

The Role of AI in Cardiovascular Event Monitoring and Early Detection: Scoping Literature Review

The Role of AI in Cardiovascular Event Monitoring and Early Detection: Scoping Literature Review

Authors of this article:

Luis B Elvas1, 2 Author Orcid Image ;   Ana Almeida3 Author Orcid Image ;   Joao C Ferreira1, 2 Author Orcid Image
Article Authors Cited by (24) Tweetations Metrics

Journals

  1. Fahmy A. Exploring the Role of AI in Predicting Chronic Disease Progression: Diabetes and Cardiovascular Diseases. Premier Journal of Public Health 2025 View
  2. Arciniegas S, Yan A, Rapoport A, Jeewa A, Muhame R, Guo L, Wolochacz A, Jessa K, Cardiff B, Tomlinson G, Witt J, Ferracci C, Sung L, Dipchand A, Nelson K. Development and prospective evaluation of a machine learning model to predict serious cardiac outcomes among paediatric cardiac inpatients. BMJ Digital Health & AI 2025;1(1):e000114 View
  3. Gaoudam N, Sakhamudi S, Kamal B, Addla N, Reddy E, Ambala M, Lavanya K, Palaparthi E, Bhattam A, Periasamy P, Sayana S, Medabala T. Wearable Devices and AI-Driven Remote Monitoring in Cardiovascular Medicine: A Narrative Review. Cureus 2025 View
  4. Natalia Kulicka , Kinga Knutelska , Tytus Tyralik , Maciej Karwat , Patrycja Jędrzejewska-Rzezak , Monika Czekalska , Aleksandra Winsyk , Joanna Węgrzecka , Paulina Gajniak , Klaudia Bilińska . FROM PREDICTION TO PREVENTION: THE ROLE OF AI IN TRANSFORMING CORONARY ARTERY DISEASE RISK ASSESSMENT. International Journal of Innovative Technologies in Social Science 2025;2(3(47)) View
  5. Henna F, Kashaf Batool S, Siddiqui H, Riaz A, Javed A, Kamran A, Faisal F, Shadab H, Qamar A, Mehboob J, Rahman R, Furqan H, Luqman M, Bacha Z. Narrative Review on Explainable Artificial Intelligence for Multimodal Risk Stratification in Coronary Artery Disease. Cardiology in Review 2025 View
  6. Sharan R, Xiong H, Cui H. Cardiac Abnormality Detection From 12-Lead ECG Using Multibranch CNN and Attention-Based Feature Fusion. IEEE Transactions on Instrumentation and Measurement 2025;74:1 View
  7. Shojaei S, Mirhosseini S, Mousavi A, Zooravar D, Ranjbar M, Aghajani S, Attar A. The effect of exosome-related therapy in cardiac revascularization procedures: a systematic review. BMC Cardiovascular Disorders 2025;25(1) View
  8. Elgendi M, Elkhalifa A, Alshehhi M, Almarri E, Khalaf K, Khandoker A, Ward R. ECG sonification methods for robust and generalizable clinical decision support. npj Digital Medicine 2025;9(1) View
  9. Carroll D, Boodhoo V, Lowe D, Carlin C. Artificial Intelligence in UK Hospital Medicine: From Innovation to Implementation. British Journal of Hospital Medicine 2025;86(12):1 View
  10. Liang C, Zhang Y, Shi J. A survey on clinical practice assisted by artificial intelligence in cardiovascular medicine. Asian Heart Journal 2025;1(3):165 View
  11. Gutierrez-Garcia J, Roman-Rangel E, Rendón-Mancha J. Deep Learning for Myocardial Infarction Detection Using Electrocardiogram Images: A Systematic Review. Mathematics 2026;14(4):613 View
  12. Gruson D, Kemaloğlu Öz T. Cardiovascular medicine in 2026: emerging technologies as a lever to reduce gaps and inequalities. Diagnosis 2026 View
  13. Korucuk N, Kömür A, İbze S, Karaman C, Gündüz E, Karaman O. Artificial intelligence-enabled printed electrochemical biosensors for detection of cardiovascular disease. Electrochimica Acta 2026;559:148581 View
  14. Parizad R, Hatwal J, Brar A, Desai R, Batta A, Mohan B. Artificial Intelligence for Cardiovascular Risk Prediction: An Umbrella Review of Applications and Translational Challenges. Vascular Health and Risk Management 2026;Volume 22:1 View
  15. Tariq A, Arikhad M, Sultana A. Machine Learning for Secure Cardiovascular Risk Assessment in Distributed Healthcare Environments. International Journal of Innovative Research in Computer Science and Technology 2026;14(1):179 View
  16. Ahmed T, Hossain M, Kasedullah M, Islam M, Hossain A, Afjal M. Accelerating the performance of machine learning classifiers using bacterial colony optimization for heart disease prediction. DIGITAL HEALTH 2026;12 View
  17. Carter J, Anoruo N, Rehman N, Otaki Y, Lydston M, Burke H. Use of Large Language Models to Extract Heart Failure Information from Electronic Health Records: A Scoping Review. Current Epidemiology Reports 2026;13(1) View
  18. Lu Y, Xu C, He J, Zhang H, Zhang L. Prognostic value of the hemoglobin, albumin, lymphocyte, and platelet score in cardiovascular disease: a systematic review and meta-analysis. Journal of Investigative Medicine 2026 View

Books/Policy Documents

  1. Denny A, Baburaj A, Kottilil R, Roy R, Jindal A, Titus A. AI Powered Drug delivery to Neuro and Cardiovascular Systems. View
  2. Vishwakarma R, Gautam P, Sahu M, Nath G, Yadav B. Advancing Early Diagnosis in Chronic Diseases. View

Conference Proceedings

  1. P K, Behera S, Rajalakshmi K, D A. 2025 9th International Conference on Inventive Systems and Control (ICISC). Epilepsy Prevention Using Enhanced Genetic Algorithm Tuned Multilayer Network View
  2. Cai Q, Kong X, Chen M, Zhou E, Liu Y, Li X. Proceedings of the 2025 6th International Symposium on Artificial Intelligence for Medical Sciences. CardioAgent: A Multi-Agent Framework for Integrated Cardiovascular Decision Support View
  3. Upadhyaya P, Tomar P. 2025 7th International Conference on Artificial Intelligence and Speech Technology (AIST). Predictive Analysis and Review of Cardiovascular Diseases in Women Using Artificial Intelligence with Clinical and Ethical Implementation Issues View
  4. Mohammed M, Wahane D, Kakani T, Gupta K, Jiwani N, Gupta U. 2026 International Conference on Smart Futuristic Technology. A Hybrid CNN–LSTM Attention Model for AI-Driven Cardiovascular Disease Detection Using Advanced ECG Signal Processing View