SynthesisObesity surgery2026
The Evolution of Bariatric and Metabolic Surgery in the Artificial Intelligence Era: A Comprehensive Systematic Review of Current Applications and Clinical Implications.
Synthesis in Obesity surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial 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.
objectiveThis systematic review aims to evaluate the utility of AI tools in BMS and summarize current applications to establish a common language for bariatric surgeons.
methodsA 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.
resultsThe 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.
conclusionAI 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.
Indexed as
Identifiers
42622983What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.