Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44791, first published .
Feasibility of Artificial Intelligence–Based Electrocardiography Analysis for the Prediction of Obstructive Coronary Artery Disease in Patients With Stable Angina: Validation Study

Feasibility of Artificial Intelligence–Based Electrocardiography Analysis for the Prediction of Obstructive Coronary Artery Disease in Patients With Stable Angina: Validation Study

Feasibility of Artificial Intelligence–Based Electrocardiography Analysis for the Prediction of Obstructive Coronary Artery Disease in Patients With Stable Angina: Validation Study

Authors of this article:

Jiesuck Park1 Author Orcid Image ;   Yeonyee Yoon1 Author Orcid Image ;   Youngjin Cho1 Author Orcid Image ;   Joonghee Kim2 Author Orcid Image

Journals

  1. Park J, Kim J, Kang S, Lee J, Hong Y, Chang H, Cho Y, Yoon Y. Artificial intelligence–enhanced electrocardiography analysis as a promising tool for predicting obstructive coronary artery disease in patients with stable angina. European Heart Journal - Digital Health 2024;5(4):444 View
  2. Cho Y, Yoon M, Kim J, Lee J, Oh I, Lee C, Kang S, Choi D. Artificial Intelligence–Based Electrocardiographic Biomarker for Outcome Prediction in Patients With Acute Heart Failure: Prospective Cohort Study. Journal of Medical Internet Research 2024;26:e52139 View
  3. Cho Y, Kim J, Kim J, Yoon Y, Jung S. Image-based ECG analyzing deep-learning algorithm to predict biological age and mortality risks: interethnic validation. Journal of Cardiovascular Medicine 2024;25(11):781 View
  4. Kalyuta T. Artificial intelligence systems for predicting disease outcomes in chronic ischemic heart disease patients who have undergone cardiac surgery in respect of anemic syndrome (review).. Russian Medicine 2024 View