Improving the detection of clinically significant steatotic liver disease using a machine learning algorithm in a real-world primary care population

2026-03-05 gastroenterology Title + abstract only

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Background and aimsPopulation screening for liver disease in high-risk groups is recommended. Community diagnosis of liver disease is a challenge due to the asymptomatic nature of disease until very advanced stages. Moreover, regional variation in testing availability can result in people with clinically significant liver disease being missed. Machine learning (ML) has been proposed as a method to reduce diagnostic error and automate screening. We present a novel machine learning derived algorit...

Improving the detection of clinically significant steatotic liver disease using a machine learning algorithm in a real-world primary care population

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