Survival machine learning model of T1 colorectal postoperative recurrence after endoscopic resection and surgical operation: a retrospective cohort study.

Objective: To construct a postoperative recurrence prediction model for patients with T1 colorectal cancer after endoscopic resection and surgical operation via survival machine learning algorithms.

Methods: Based on two tertiary-level affiliated hospitals, case data of 580 patients with T1 colorectal cancer treated by endoscopic resection and surgery were obtained, and patients' personal information, treatment modalities, and pathology-related information were extracted. After Boruta's algorithmic feature selection, predictors with significant contributions were identified.