A study evaluated the use of an AI-model applied to 12-lead ECG to detect undiagnosed advanced chronic liver disease (cirrhosis) in a pragmatic, cluster-randomized design involving 45 clinics and 15,596 visits.[1] The AI-screening solution was integrated into routine ambulatory practice and compared with standard workflow without AI.[1] There was a significant increase in new diagnoses of advanced chronic liver disease in the AI-ECG group compared to the non-AI group.[1][2] Clinicians in the study used AI results for follow-up verification tests, with diagnosis confirmed using protocol-validated imaging or blood tests.[2] The study involved 248 clinicians within the Mayo Clinic and Mayo Clinic Health System who implemented the AI-ECG model in routine examinations.[2] The model has been trained on thousands of ECG recordings, and previous internal validations have shown the ability to recognize patterns associated with advanced liver disease.[1] The study documents that the implementation of AI-ECG in primary care leads to a higher detection of hitherto undiagnosed cirrhosis, while new diagnoses were, according to the author of the study, approximately twice the standard procedure.[2]