ArticleObesity surgery2025
The Performance of Artificial Intelligence in One Anastomosis Gastric Bypass Surgery: Comparative Efficacy of ChatGPT-4.0, ChatGPT-Omni, and Gemini AI.
Article in Obesity surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Large language models in obesity: a systematic review.International journal of obesity (2005) · 2026Pooled it
- Article
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1 author.
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Abstract
backgroundThe integration of artificial intelligence (AI) into medical practice opens up new frontiers for decision support, especially in intricate surgical procedures like one-anastomosis gastric bypass (OAGB). This study was designed to showcase the potential and performance of three AI models-ChatGPT-4.0, ChatGPT-Omni, and Gemini AI-in tackling complex clinical queries related to OAGB, thereby paving the way for a more efficient and effective surgical practice.
methodsThe study utilized a comprehensive query evaluation methodology comprising 180 questions for ChatGPT-4.0, ChatGPT-Omni, and Gemini AI models, equally divided among true/false, multiple-choice, open-ended, and case-scenario queries. These questions covered various aspects of OAGB surgery, including preoperative assessment, surgical technique, management of complications, and long-term outcomes.
resultsChatGPT-Omni showed higher accuracy rates than Gemini AI and ChatGPT-4.0 in most question formats and difficulty levels (p < 0.0001). However, the performance gap varied depending on the complexity and type of the queries. In true-false and multiple-choice formats, ChatGPT-Omni excelled, particularly in complex scenarios (p = 0.017). With a mean of 5.62 on a six-point scale, ChatGPT-Omni demonstrated exceptional capability in providing accurate and comprehensive answers to both open-ended and case scenarios. ChatGPT-Omni demonstrated the highest performance metrics, including precision (0.947), recall (0.857), and F1-score (0.9), although these values were dependent on the specific query format and type.
conclusionsWhile ChatGPT-Omni demonstrated superior accuracy in many clinical queries related to OAGB, especially in simpler decision-making scenarios, it is crucial to underscore the need for additional validation in complex clinical settings. This cautionary note serves as a reminder of the current limitations of AI in surgery and the importance of ongoing research and validation.
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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.