Artificial Intelligence in Bariatric Surgery: Optimizing Personalized Decision-Making, Predictive Monitoring, and Postoperative Outcomes

Résumé fourni par la source

Bariatric surgery is an effective treatment for morbid obesity, but patient outcomes differ greatly because of a variety of phenotypes, comorbidities, and postoperative adherence. In bariatric care, artificial intelligence (AI) and machine learning (ML) are becoming revolutionary tools because traditional predictive models based on BMI and demographic variables are unable to account for these complexities. To put it simply, AI is a branch of computer science that enables machines to perform tasks that typically require human intelligence. On the other hand, ML is a subset of AI, where systems learn from data to improve predictions. This study investigates how AI can be used to enhance dynamic, patient-centered follow-up, predict postoperative complications, and improve surgical decision-making. AI can customize interventions, lower complications, and promote long-term weight loss by combining multidimensional data, such as metabolic profiles, behavioral feedback, and phenotypic traits. This study demonstrates how precision powered by AI is laying the groundwork for bariatric surgery in the future.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.