Work

HRS scientific statement on artificial intelligence integration framework into clinical electrophysiology workflows

Year: 2026

Type: article

Source: Heart Rhythm

DOI: 10.1016/j.hrthm.2026.04.013

Authors: Antonis A. Armoundas, Jennifer N. Avari Silva, Tina Baykaner, Neal Bhatia, Nino Isakadze, Krishna Pundi, Konstantinos C. Siontis, Peem Lorvidhaya, Jason G. Andrade, Matthew M. Kalscheur, Peter A. Noseworthy, Michael A. Rosenberg

Institutions: Broad Institute, Massachusetts General Hospital, Massachusetts Institute of Technology, Washington University in St. Louis, Stanford Medicine, Stanford University, Emory University, Johns Hopkins University, Johns Hopkins Medicine, VA Palo Alto Health Care System, Mayo Clinic, Mary Washington Hospital, Vancouver General Hospital, University of Wisconsin–Madison, University of Colorado Anschutz

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W7154996576

FWCI: 7.787

Cites: 62

Cited by: 4

Related to: 10