Published on in Vol 9, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34058, first published .
Understanding Cardiology Practitioners’ Interpretations of Electrocardiograms: An Eye-Tracking Study

Understanding Cardiology Practitioners’ Interpretations of Electrocardiograms: An Eye-Tracking Study

Understanding Cardiology Practitioners’ Interpretations of Electrocardiograms: An Eye-Tracking Study

Journals

  1. Tahri Sqalli M, Aslonov B, Gafurov M, Nurmatov S. Humanizing AI in medical training: ethical framework for responsible design. Frontiers in Artificial Intelligence 2023;6 View
  2. Hu L, Huang S, Liu H, Du Y, Zhao J, Peng X, Li D, Chen X, Yang H, Kong L, Tang J, Li X, Liang H, Liang H. A cardiologist-like computer-aided interpretation framework to improve arrhythmia diagnosis from imbalanced training datasets. Patterns 2023;4(9):100795 View
  3. Tahri Sqalli M, Aslonov B, Gafurov M, Mukhammadiev N, Sqalli Houssaini Y. Eye tracking technology in medical practice: a perspective on its diverse applications. Frontiers in Medical Technology 2023;5 View
  4. Khalifa A, Khidr S, Hassan A, Mohammed H, El-Sharkawi M, Fadle A. Can Orthopaedic Surgeons adequately assess an Electrocardiogram (ECG) trace paper? A cross sectional study. Heliyon 2023;9(12):e22617 View
  5. McKenna S, McCord N, Diven J, Fitzpatrick M, Easlea H, Gibbs A, Mitchell A. Evaluating the impacts of digital ECG denoising on the interpretive capabilities of healthcare professionals. European Heart Journal - Digital Health 2024;5(5):601 View

Books/Policy Documents

  1. Sqalli M, Al-Thani D, Elshazly M, Al-Hijji M. Persuasive Technology. View
  2. Sqalli M, Al-Thani D, Elshazly M, Al-Hijji M, Alahmadi A, Houssaini Y. Medical Imaging and Computer-Aided Diagnosis. View