GPT and metabolic dysfunction-associated steatotic liver disease: Ma et al. [94] developed a machine learning predictive model for NAFLD, by selecting 5 features such as weight, TG levels, ALT, GGT, and serum uric acid levels that provided the most accurate predictions in their Bayesian network model achieving an accuracy rate of 83%, a specificity of 0.878, and a sensitivity of 0.675.