Artificial intelligence analysis of sinus rhythm ECGs can detect occult atrial fibrillation and stratify future risk with moderate-to-high accuracy across multiple populations.
Does AI-based analysis of sinus rhythm ECGs improve the detection and prediction of atrial fibrillation?
AI analysis of sinus rhythm ECGs shows promise for detecting and predicting atrial fibrillation, but prospective clinical trials are needed before widespread clinical adoption.
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AI-based analysis of sinus rhythm ECGs can detect occult AF and stratify future AF risk with moderate-to-high accuracy across multiple populations and healthcare systems. However, rigorous prospective trials, evaluating clinical benefit, cost-effectiveness, calibration across demographic groups, and real-world implementation, are required before broad adoption in clinical practice.
Mrak et al. (Sat,) reported a other. Artificial intelligence analysis of sinus rhythm ECGs can detect occult atrial fibrillation and stratify future risk with moderate-to-high accuracy across multiple populations.