Integrating Machine Learning and Dynamic Digital Follow-up for Enhanced Prediction of Postoperative Complications in Bariatric Surgery.
Journal:
Obesity surgery
Published Date:
Jun 1, 2025
Abstract
BACKGROUND: Traditional risk models, such as POSSUM and OS-MS, have limited accuracy in predicting complications after bariatric surgery. Machine learning (ML) offers new opportunities for personalized risk assessment by incorporating artificial intelligence (AI). This study aimed to develop and evaluate two ML-based models: one using preoperative clinical data and another integrating postoperative data from a mobile application.