An AI tool accurately detected structural heart disease from smartwatch single-lead ECGs in a 600-person prospective trial.
Key Details
- 1AI model was trained using 266,000 12-lead ECGs from 110,000 patients and validated on large external cohorts.
- 2Prospective real-world testing was performed with 600 adults using smartwatch-recorded single-lead ECGs.
- 3Algorithm achieved 88% accuracy (AUC) in smartwatch data; sensitivity was 86% and negative predictive value 99%.
- 4Diseases detected included weakened pumping, valve damage, or thickened heart muscle—most commonly found with cardiac ultrasound (echo).
- 5Preliminary results were presented at AHA Scientific Sessions 2025 and have not yet been peer-reviewed.
Why It Matters
Wearable devices leveraging AI may democratize early detection of serious heart conditions, traditionally requiring advanced imaging. This signals a potential paradigm shift in accessible screening workflows, informing radiology and cardiology practice.
Source
EurekAlert
Related News
•EurekAlert
Optical AI Chip Boosts Real-Time Dry Eye Gland Diagnosis Accuracy
A new metasurface spectral AI chip enables rapid, accurate diagnosis of meibomian gland dysfunction (MGD) from tissue samples, achieving 96.22% accuracy.
•EurekAlert
New AI Vision-Language Model Enhances Chest CT Diagnostics
Researchers developed an interpretable AI model that uses visual question answering to generate detailed diagnostic findings from chest CT scans, aimed at improving lung cancer diagnosis.
•EurekAlert
AI Analyzes 66,000 MRI Scans to Map Body Composition Risks
Researchers used AI to analyze over 66,000 whole-body MRI scans, creating a detailed body composition reference map linked to health risks.