Published on in Vol 10, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29434, first published .
Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View

Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View

Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View

Journals

  1. Huang J, Wang J, Ramsey E, Leavey G, Chico T, Condell J. Applying Artificial Intelligence to Wearable Sensor Data to Diagnose and Predict Cardiovascular Disease: A Review. Sensors 2022;22(20):8002 View
  2. Leiner J, König S, Mouratis K, Kim I, Schmitz P, Joshi T, Schanner C, Wohlrab L, Hohenstein S, Pellissier V, Nitsche A, Kuhlen R, Hindricks G, Bollmann A. A Digital Infrastructure for Cardiovascular Patient Care Based on Mobile Health Data and Patient-Reported Outcomes: Concept Details of the Helios TeleWear Project Including Preliminary Experiences. JMIR Formative Research 2023;7:e41115 View
  3. Chidambaram S, Maheswaran Y, Patel K, Sounderajah V, Hashimoto D, Seastedt K, McGregor A, Markar S, Darzi A. Using Artificial Intelligence-Enhanced Sensing and Wearable Technology in Sports Medicine and Performance Optimisation. Sensors 2022;22(18):6920 View
  4. Moses J, Adibi S, Angelova M, Islam S. Smart Home Technology Solutions for Cardiovascular Diseases: A Systematic Review. Applied System Innovation 2022;5(3):51 View
  5. Andayeshgar B, Abdali-Mohammadi F, Sepahvand M, Almasi A, Salari N. Arrhythmia detection by the graph convolution network and a proposed structure for communication between cardiac leads. BMC Medical Research Methodology 2024;24(1) View
  6. Foote H, Cohen-Wolkowiez M, Lindsell C, Hornik C. Applying Artificial Intelligence in Pediatric Clinical Trials: Potential Impacts and Obstacles. The Journal of Pediatric Pharmacology and Therapeutics 2024;29(3):336 View
  7. Scholte N, van Ravensberg A, Shakoor A, Boersma E, Ronner E, de Boer R, Brugts J, Bruining N, van der Boon R. A scoping review on advancements in noninvasive wearable technology for heart failure management. npj Digital Medicine 2024;7(1) View
  8. Siira E, Johansson H, Nygren J. Mapping and Summarizing the Research on AI Systems for Automating Medical History Taking and Triage: Scoping Review. Journal of Medical Internet Research 2025;27:e53741 View
  9. Foote H, Hong C, Anwar M, Borentain M, Bugin K, Dreyer N, Fessel J, Goyal N, Hanger M, Hernandez A, Hornik C, Jackman J, Lindsay A, Matheny M, Ozer K, Seidel J, Stockbridge N, Embi P, Lindsell C. Embracing Generative Artificial Intelligence in Clinical Research and Beyond. JACC: Advances 2025;4(3):101593 View
  10. Gradl L, Reis L, Buettner R. Industrial Maturity of Machine Learning Solutions Within the Food Industry. IEEE Access 2025;13:62831 View
  11. Mishkin I, Koncevaya A, Drapkina O. Prediction of cardiovascular events with using proportional risk models and machine learning algorithms: a systematic review. The European Physical Journal Special Topics 2025 View
  12. Ahmad O, Ibrahim R, Odunsi D, Mohammed M, Mathew B, Touny M, Grewal B, Bhanot S, Bodapati N, Thomas G, NV S, Masood L, Morani Z. Role of Mobile Health and Wearable Devices in Cardiovascular Disease Prevention: A Comprehensive Review. Cureus 2025 View

Books/Policy Documents

  1. Zinzuwadia A, Goldberg J, Hanson M, Wessler J. Emerging Practices in Telehealth. View
  2. Leigard E, Breteler M, van Loon K. Textbook of Rapid Response Systems. View

Conference Proceedings

  1. Baikuvekov M, Tursynova A, Yespayev G. 2024 IEEE 4th International Conference on Smart Information Systems and Technologies (SIST). A Deep Learning for Cardiovascular Diseases Detection on Wearable Devices Data View
  2. Verma S, Midha S, Dhole M, Patel R. 2024 International Conference on Sustainable Communication Networks and Application (ICSCNA). Enhancing Cardiovascular Health Monitoring and Diagnosis through Wearable Sensors with Reinforcement Learning-Driven Predictive Models View

Dissertations

  1. . Wearables in Healthcare: Popular Topics and Sentiments in Reddit and a Preliminary Quantitative Study on Health Professionals’ Wearable Adoption. View