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

Mobile Health (mhealth) (3464) Novel Sensors and Data Acquisition Methods in Cardiology (225) Decision Support for Health Professionals (1539) New Methods (1134) Wearable Devices and Sensors (1133) Machine Learning (2076) Artificial Intelligence (2129) mHealth for Diagnosis (81) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1732) mHealth for Telemedicine and Homecare (531) e-Cardiology and Telemonitoring in Cardiology (221) Myocardial Infarction (Heart Attack) (56)

Published on in Vol 23, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31129, first published .
Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals—Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study

Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals—Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study

Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals—Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study

Authors of this article:

Changho Han1 Author Orcid Image ;   Youngjae Song2 Author Orcid Image ;   Hong-Seok Lim3 Author Orcid Image ;   Yunwon Tae2 Author Orcid Image ;   Jong-Hwan Jang1 Author Orcid Image ;   Byeong Tak Lee2 Author Orcid Image ;   Yeha Lee2 Author Orcid Image ;   Woong Bae2 Author Orcid Image ;   Dukyong Yoon1, 4 Author Orcid Image
Article Authors Cited by (19) Tweetations (28) Metrics

Journals

  1. Petmezas G, Stefanopoulos L, Kilintzis V, Tzavelis A, Rogers J, Katsaggelos A, Maglaveras N. State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review. JMIR Medical Informatics 2022;10(8):e38454 View
  2. Lee C, Lee C, Fernando C, Chow C. Comparison of Apple Watch vs KardiaMobile: A Tale of Two Devices. CJC Open 2022;4(11):939 View
  3. Li K, Elgalad A, Cardoso C, Perin E. Using the Apple Watch to Record Multiple-Lead Electrocardiograms in Detecting Myocardial Infarction: Where Are We Now?. Texas Heart Institute Journal 2022;49(4) View
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  5. Kampaktsis P, Emfietzoglou M, Al Shehhi A, Fasoula N, Bakogiannis C, Mouselimis D, Tsarouchas A, Vassilikos V, Kallmayer M, Eckstein H, Hadjileontiadis L, Karlas A. Artificial intelligence in atherosclerotic disease: Applications and trends. Frontiers in Cardiovascular Medicine 2023;9 View
  6. Pap I, Oniga S. A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence. International Journal of Environmental Research and Public Health 2022;19(18):11413 View
  7. 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
  8. Han C, Kang K, Kim T, Uhm J, Park J, Jung I, Kim M, Bae S, Lim H, Yoon D. Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification. Frontiers in Cardiovascular Medicine 2022;9 View
  9. Li K, Morales-Garza M, Cardoso C, Moctezuma-Ramirez A, Burman A, Titus J, Elgalad A, Perin E. Early Changes in Acute Myocardial Infarction in Pigs: Achieving Early Detection with Wearable Devices. Diagnostics 2023;13(6):1006 View
  10. Lee S, Back J, Joo H, Lim D, Lee J, Lee H. Simultaneous detection method for two cardiac disease protein biomarkers on a single chip modified with mixed aptamers using surface plasmon resonance. Talanta 2024;267:125232 View
  11. Lee J, Hwang Y, Park S. Rationale and Design of a Wearable Cardiopulmonary Monitoring System for Improving the Efficiency of Critical Care Monitoring. Applied Sciences 2023;13(24):13101 View
  12. Nie S, Zhang S, Zhao Y, Li X, Xu H, Wang Y, Wang X, Zhu M. Machine Learning Applications in Acute Coronary Syndrome: Diagnosis, Outcomes and Management. Advances in Therapy 2025;42(2):636 View
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  14. Marzoog B, Kopylov P. Volatilome and machine learning in ischemic heart disease: Current challenges and future perspectives. World Journal of Cardiology 2025;17(4) View
  15. Medina-Avelino J, Silva-Bustillos R, Holgado-Terriza J. Are Wearable ECG Devices Ready for Hospital at Home Application?. Sensors 2025;25(10):2982 View
  16. Bartusik-Aebisher D, Rogóż K, Aebisher D. Artificial Intelligence and ECG: A New Frontier in Cardiac Diagnostics and Prevention. Biomedicines 2025;13(7):1685 View
  17. Kong V, Kim K, Shon H. Deep learning-based prognosis of major adverse cardiac events in patients with acute myocardial infarction: a retrospective observational study in the Republic of Korea. Osong Public Health and Research Perspectives 2025;16(4):333 View
  18. Han C, Soh S, Park J, Pak H, Yoon D. Artificial Intelligence–Based Electrocardiogram Model as a Predictor of Postoperative Atrial Fibrillation Following Cardiac Surgery: Retrospective Cohort Study. Journal of Medical Internet Research 2025;27:e77164 View

Books/Policy Documents

  1. Malanin V, Chaikovsky I. Proceedings of Ninth International Congress on Information and Communication Technology. View