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

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
  4. Melzi P, Tolosana R, Vera-Rodriguez R. ECG Biometric Recognition: Review, System Proposal, and Benchmark Evaluation. IEEE Access 2023;11:15555 View
  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

Books/Policy Documents

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