Postoperative survival prediction in pancreatic ductal adenocarcinoma and adenosquamous carcinoma: development of the machine learning-based model

The XGBoost-based ML model developed in this study integrates clinical, laboratory, and pathological data, providing superior predictive performance and good interpretability for assessing postoperative survival in PC. This model not only offers robust predictions for the general population but also effectively identifies risk variations across pathological subtypes. It holds substantial clinical value for postoperative risk stratification and decision making in treatment planning.