The Evolution of Bariatric and Metabolic Surgery in the Artificial Intelligence Era: A Comprehensive Systematic Review of Current Applications and Clinical Implications.
Mohammed S Foula, Omar A Bamalan, Ahmed Foula et al.
✦ AI-curated · Sources linked
In 30 seconds
This systematic review assessed applications of artificial intelligence (AI) in bariatric and metabolic surgery (BMS), including preoperative, intraoperative, postoperative, and large language model uses. Searches of PubMed, Cochrane, and Web of Science identified 840 studies, with 25 more found through citation screening; 88 studies were included after screening. The authors rated the evidence overall moderate to high quality. They concluded that AI currently serves as a supportive rather than decisive tool in BMS, with large language models warranting caution when used for preliminary health education.
Key findings
- The review included 88 studies covering AI applications before, during, and after BMS, as well as large language models.
- Quality assessment indicated that the included evidence was overall moderate to high quality.
- The authors characterized AI as supportive rather than decisive in BMS and advised caution with large language models for preliminary health education.
Why it matters
The review maps a developing evidence base across several stages of bariatric care and clarifies that current AI applications are intended to assist, not replace, clinical judgement. Its cautious framing is relevant as clinicians encounter AI tools, particularly language models used for health education. The authors also identify AI literacy, collaboration, and registries as priorities for developing the field.
What to keep in mind
The authors note that published evidence remains limited; the review also reflects studies available through October 2025.