QR Code (код быстрого отклика)

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)...

Полное описание

Сохранить в:
Главные авторы: 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
Формат: Artigo
Язык:Inglês
Опубликовано: Elsevier 2025-09-01
Серии:JACC: Advances
Предметы:
artificial intelligence
coronary artery disease
electrocardiogram
prediction
Online-ссылка:http://www.sciencedirect.com/science/article/pii/S2772963X2500465X
Метки: Добавить метку
Нет меток, Требуется 1-ая метка записи!

Схожие документы