Artificial Intelligence-Enabled ECG Analysis to Predict Incident Heart Failure

20260 citationsJournal Articlegreen Open Access

Authors

Shaan Khurshid · Broad Institute

Samuel F. Friedman · Broad Institute

S Kany · Broad Institute

Valentina D’Souza · Boston Foundation

Athar Roshandelpoor · Beth Israel Deaconess Medical Center

Leah Kosyakovsky · Beth Israel Deaconess Medical Center

Mitra Chitsazan ·

Abstract

ECG2HF is a publicly available 12-lead ECG-based artificial intelligence model that discriminates the risk of future HF with favorable and consistent performance across 3 large health care samples from the northeastern United States. ECG2HF may enable efficient prioritization of high-risk individuals for HF-related preventive measures.

Topics & Keywords

ECG Monitoring and Analysis Heart Failure Treatment and Management Atrial Fibrillation Management and Outcomes

UN Sustainable Development Goals

Gender equality

Publication Details

Published in: Circulation Heart Failure

DOI: 10.1161/circheartfailure.125.013927

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