Artificial Intelligence-Powered Decision Support in Metabolic and Bariatric Surgery and Endobariatrics

Qaviullah Mian; Pedro Augusto Vega Guillen; Mohammed Nooruddin; Lina Alami; Bryan Vintimilla; J. Castillo; Sara Rachel Shajee and; Murtaja Satea; Murtaja Satea Shafeea · IntechOpen eBooks (2026) · DOI: 10.5772/intechopen.1015203

Resumen

Artificial intelligence (AI) algorithms have transformed obesity care and metabolic and bariatric surgery by augmenting clinical decision-making in this era of increasing complexity. From patient selection and comorbidity profiling, through risk stratification in the preoperative settings and real-time intraoperative enhancements like tissue recognition and anastomotic quality assessment, to forecasting postoperative complications and long-term outcomes, this chapter examines the details of how AI-driven systems can assist in the aforementioned workflow. With the evidence base growing recently more than ever, multiple machine learning models have provided a basis for risk calculators that have demonstrated promising accuracy in predicting outcomes in bariatric cohorts. This chapter outlines the key data sources, modeling strategies, the process for embedding AI into the multidisciplinary workflow of metabolic and bariatric diseases, and future trends. We address special considerations in the endobariatric domain (minimally invasive, endoscopic procedures) and highlight the regulatory, ethical, and educational frameworks necessary for safe deployment. With a focus on clinical relevance and surgical applicability, the chapter aims to equip bariatric and endobariatric teams with a roadmap to harness AI-powered decision support for improved patient-centered outcomes. Finally, however, as with any technological shiift, real-world constraints always exist that require an inclusive approach to ensure no crucial details are overlooked. Therefore, this chapter also analyzes the ethical and financial implications of the implementation of AI in bariatric surgery and endobariatrics.

Instituciones: Universidad Peruana de Ciencias Aplicadas