Published Scientific Evidence
Anumana’s ECG-AI® technology is supported by one of the most extensive evidence bases in cardiovascular AI. This library provides direct access to our peer-reviewed validation studies and broader body of clinical research.
February
16
2026
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European Heart Journal
Artificial intelligence 12-lead electrocardiography to determine atrial fibrillation risk among UK Biobank participants with predisposing conditions
Abstract Background Artificial intelligence electrocardiography (AI-ECG) algorithms are emerging tools for identifying individuals at risk of atrial fibrillation (AF). We evaluated the predictive performance of a validated AI-ECG algorithm for…
January
16
2026
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JACC
Multisite, External Validation of an AI-Enabled ECG Algorithm for Detection of Low Ejection Fraction
Abstract Background: Low left ventricular ejection fraction (LEF) can progress undiagnosed. Artificial intelligence–based electrocardiogram (ECG-AI) screening may provide a scalable means to detect LEF.Objectives: The purpose of this study was…