Scalable Risk Stratification for Heart Failure Using Artificial Intelligence applied to 12-lead Electrocardiographic Images: A Multinational Study.

Lovedeep Singh Dhingra Arya Aminorroaya Veer SanghaAline Pedroso CamargosFolkert W AsselbergsLuisa Campos Caldeira BrantSandhi M BarretoAntonio Luiz P RibeiroHarlan M Krumholz Evangelos K Oikonomou Rohan Khera

Published in: medRxiv : the preprint server for health sciences (2024)

An AI model applied to images of 12-lead ECGs can identify those at elevated risk of HF across multinational cohorts. As a digital biomarker of HF risk that requires just an ECG image, this AI-ECG approach can enable scalable and efficient screening for HF risk.

Keyphrases

artificial intelligence
deep learning
heart failure
big data
machine learning
acute heart failure
convolutional neural network
heart rate variability
left ventricular
heart rate
atrial fibrillation
blood pressure
cardiac resynchronization therapy
left atrial