Key result
An electrocardiogram machine learning model significantly increased new diagnoses of chronic liver disease with advanced fibrosis compared to usual care (OR 2.09).
Why the study?
Does an ECG machine learning model improve the detection of chronic liver disease in primary care compared to usual care?
Does an ECG machine learning model improve the detection of chronic liver disease in primary care compared to usual care?
Odds Ratio: 2.09 (95% CI 1.22–3.55)
An artificial intelligence-augmented ECG model can significantly improve the detection of previously undiagnosed chronic liver disease with advanced fibrosis in primary care, though substantial implementation barriers remain.
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Keith et al. (2026) conducted an editorial in Chronic liver disease. Electrocardiogram machine learning (ECG-ML) model vs. Usual care was evaluated on New diagnoses of chronic liver disease with advanced fibrosis (OR 2.09, 95% CI 1.22-3.55). An electrocardiogram machine learning model significantly increased new diagnoses of chronic liver disease with advanced fibrosis compared to usual care (OR 2.09).
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