Obesity surgery · 2026
The Evolution of Bariatric and Metabolic Surgery in the Artificial Intelligence Era: A Comprehensive Systematic Review of Current Applications and Clinical Implications.
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Foula Mohammed S, Bamalan Omar A, Foula Ahmed, Eldamati Ahmed M, Alratrout Hefzi A, AlQatari Abdullah A, Alsaleem Hassan A, Aldabaeab Abdulaziz E, Foula Hassan, Zakaria Hazem M, Alarfaj Mosab A, Sharroufna Mohammed J, Nwesar Fayrouz A
Аннотация
BACKGROUND: Artificial intelligence (AI) uses in the field of bariatric and metabolic surgery (BMS) have evolved over the past few years. However, published evidence remains limited. AI generally refers to computer systems capable of performing tasks that require human intelligence and cognitive functions.
OBJECTIVE: This systematic review aims to evaluate the utility of AI tools in BMS and summarize current applications to establish a common language for bariatric surgeons.
METHODS: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane Handbook for Systematic Reviews of Interventions guidelines. Studies indexed in PubMed, Cochrane, and Web of Science databases were identified using appropriate keywords related to obesity, bariatric procedures, and AI tools from inception until October 2025. Relevant studies' reference lists were also screened. The quality of included studies was assessed using the Joanna Briggs Institute critical appraisal tools.
RESULTS: The literature search identified 840 studies, with an additional 25 studies identified through citation screening. After removing duplicates and screening, 88 studies were included, categorized into preoperative, intraoperative, and postoperative AI uses as well as large language models uses. Quality assessment showed overall moderate to high quality.
CONCLUSION: AI uses in BMS remains a supportive rather than a decisive tool. When applied appropriately, AI can assist surgeons and patients. LLMs should be used cautiously for preliminary health education. Societal initiatives should direct future efforts to address research gaps. Improving surgeon AI literacy, collaboration with AI specialists, and establishing national registries will maximize AI's potential.
OBJECTIVE: This systematic review aims to evaluate the utility of AI tools in BMS and summarize current applications to establish a common language for bariatric surgeons.
METHODS: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane Handbook for Systematic Reviews of Interventions guidelines. Studies indexed in PubMed, Cochrane, and Web of Science databases were identified using appropriate keywords related to obesity, bariatric procedures, and AI tools from inception until October 2025. Relevant studies' reference lists were also screened. The quality of included studies was assessed using the Joanna Briggs Institute critical appraisal tools.
RESULTS: The literature search identified 840 studies, with an additional 25 studies identified through citation screening. After removing duplicates and screening, 88 studies were included, categorized into preoperative, intraoperative, and postoperative AI uses as well as large language models uses. Quality assessment showed overall moderate to high quality.
CONCLUSION: AI uses in BMS remains a supportive rather than a decisive tool. When applied appropriately, AI can assist surgeons and patients. LLMs should be used cautiously for preliminary health education. Societal initiatives should direct future efforts to address research gaps. Improving surgeon AI literacy, collaboration with AI specialists, and establishing national registries will maximize AI's potential.