Electrocardiogram-Based Artificial Intelligence to Identify Coronary Artery Disease

Background: Coronary artery disease (CAD) results in substantial morbidity and mortality. Objectives: The purpose of this study was to develop a deep learning model to detect CAD defined using diagnostic codes (“ECG2CAD”) and identify people at risk for adverse events using electrocardiograms (ECGs)...

Cijeli opis

Bibliografski detalji

Glavni autori:	Shinwan Kany, MD, MSc, Samuel F. Friedman, PhD, Mostafa Al-Alusi, MD, Shaan Khurshid, MD, MPH, Joel T. Rämö, MD, PhD, Daniel Pipilas, MD, James P. Pirruccello, MD, Christopher Reeder, PhD, Anthony A. Philippakis, MD, PhD, Jennifer E. Ho, MD, Mahnaz Maddah, PhD, Patrick T. Ellinor, MD, PhD, Akl C. Fahed, MD, MPH
Format:	Artigo
Jezik:	Inglês
Izdano:	Elsevier 2025-09-01
Serija:	JACC: Advances
Teme:	artificial intelligence coronary artery disease electrocardiogram prediction
Online pristup:	http://www.sciencedirect.com/science/article/pii/S2772963X2500465X
Oznake:	Dodaj oznaku Bez oznaka, Budi prvi tko označuje ovaj zapis!