Work

AI-Enabled Echocardiography Identifies Prominent Epicardial Adipose Tissue Associated With an Adverse Cardiometabolic Profile

Year: 2026

Type: article

Source: Journal of the American College of Cardiology

DOI: 10.1016/j.jacc.2026.10.066

Authors: Arya Aminorroaya, Andreas Coppi, Robert L. McNamara, Joao A.C. Lima, Harlan M. Krumholz, Charalambos Antoniades, Rohan Khera, Evangelos K. Oikonomou

Institutions: Yale University, Johns Hopkins University, Johns Hopkins Medicine, Yale New Haven Hospital, University of Oxford

Language: English

Topic: Cardiovascular Disease and Adiposity

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: American Heart Association, National Institutes of Health, National Institute on Aging, National Heart, Lung, and Blood Institute, National Center for Advancing Translational Sciences

Awards: Deep learning enhanced detection and personalized monitoring of aortic stenosis - The DETECT-AS Study, Translating Personalized Inference from Randomized Clinical Trials to Real-World Cardiovascular Care, Evaluating and Improving Utilization of Evidence-Based Medical Therapy in Patients with Heart Failure using Automated Tools in the Electronic Health Record, Yale Clinical and Translational Science Award, Claude D. Pepper Older Americans Independence Center at Yale

OpenAlex ID: W7170875842

FWCI:

Cites: 2

Cited by:

Related to: 10