Published on in Vol 6, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35396, first published .
Diagnosis of Atrial Fibrillation Using Machine Learning With Wearable Devices After Cardiac Surgery: Algorithm Development Study

Diagnosis of Atrial Fibrillation Using Machine Learning With Wearable Devices After Cardiac Surgery: Algorithm Development Study

Diagnosis of Atrial Fibrillation Using Machine Learning With Wearable Devices After Cardiac Surgery: Algorithm Development Study

Journals

  1. Moshawrab M, Adda M, Bouzouane A, Ibrahim H, Raad A. Smart Wearables for the Detection of Cardiovascular Diseases: A Systematic Literature Review. Sensors 2023;23(2):828 View
  2. Manetas-Stavrakakis N, Sotiropoulou I, Paraskevas T, Maneta Stavrakaki S, Bampatsias D, Xanthopoulos A, Papageorgiou N, Briasoulis A. Accuracy of Artificial Intelligence-Based Technologies for the Diagnosis of Atrial Fibrillation: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine 2023;12(20):6576 View
  3. Kim D, Min J, Ko S. Recent Developments and Future Directions of Wearable Skin Biosignal Sensors. Advanced Sensor Research 2024;3(2) View
  4. Ghomrawi H, O’Brien M, Carter M, Macaluso R, Khazanchi R, Fanton M, DeBoer C, Linton S, Zeineddin S, Pitt J, Bouchard M, Figueroa A, Kwon S, Holl J, Jayaraman A, Abdullah F. Applying machine learning to consumer wearable data for the early detection of complications after pediatric appendectomy. npj Digital Medicine 2023;6(1) View
  5. El-Sherbini A, Shah A, Cheng R, Elsebaie A, Harby A, Redfearn D, El-Diasty M. Machine Learning for Predicting Postoperative Atrial Fibrillation After Cardiac Surgery: A Scoping Review of Current Literature. The American Journal of Cardiology 2023;209:66 View
  6. Jiang Z, Van Zoest V, Deng W, Ngai E, Liu J. Leveraging Machine Learning for Disease Diagnoses Based on Wearable Devices: A Survey. IEEE Internet of Things Journal 2023;10(24):21959 View
  7. Hernandez J, Shah K, Spayd R, Davis S. Is wearable technology accurate at detecting atrial fibrillation?. Evidence-Based Practice 2024;27(5):9 View
  8. Ding C, Xiao R, Wang W, Holdsworth E, Hu X. Photoplethysmography based atrial fibrillation detection: a continually growing field. Physiological Measurement 2024;45(4):04TR01 View

Books/Policy Documents

  1. Chung C, Roy V, Tse G, Liu H. Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing. View