Using artificial intelligence to evaluate adherence to best practices in one anastomosis gastric bypass: first steps in a real-world setting

The model appears to have high accuracy, sensitivity, and positive predictive value for evaluating adherence to best practices for safety in OAGB. Considering the paucity of negative estimates in our study, more low-performance cases are needed to reliably define the model's specificity and negative predictive value. Adding more best practices, tested in multi-center studies will enable cross-border standardization of the procedure.