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Abstract Objective: To construct and internally validate a machine learning-assisted diagnostic model that identifies gastroesophageal varices (GEV) in patients with cirrhosis from routinely collected clinical and laboratory data. Methods: We retrospectively analyzed 5,037 patients with cirrhosis who underwent endoscopy from January 2024 through May 2026. Random allocation at a 7:3 ratio produced a training set (n = 3,526) and a validation set (n = 1,511).
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
