Work

Reimagining atrial fibrillation screening beyond age-based thresholds using AI

Year: 2026

Type: article

Abstract: Atrial fibrillation (AF) affects over 50 million people worldwide and carries substantial downstream morbidity, mortality, and cost. Yet many contemporary screening programs rely primarily on age thresholds—an approach that is operationally simple but can be imprecise for identifying near-term risk. AI applied to handheld single-lead ECGs can predict incident AF with accuracy similar to established clinical risk scores, but real-world deployment remains limited by signal noise, workflow complexity, and unclear risk thresholds.

Source: npj Digital Medicine

DOI: 10.1038/s41746-026-02485-w

Authors: Tara P. Menon, Arjun Mahajan, Dylan Powell

Institutions: Carilion Clinic, Virginia Tech, Harvard University, University of Stirling

Language: English

Topic: Atrial Fibrillation Management and Outcomes

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $4,090