A new machine learning tool helps surgeons determine the optimal timing for cholecystectomy after transcutaneous gallbladder drainage in elderly acute cholecystitis patients, improving surgical outcomes.

• Random forest model achieved an AUC of 0.914, outperforming other models for predicting surgery delays.
• Key predictors for delayed surgery include age, gallbladder wall thickness, and white blood cell count.

Using this online calculator can enhance patient selection and streamline decision-making for timely surgical intervention.