Evidence map›Paper›PMID 39733375›Full record

ArticleObesity surgery2025

Evaluating AI Capabilities in Bariatric Surgery: A Study on ChatGPT-4 and DALL·E 3's Recognition and Illustration Accuracy.

Mohammad Mahjoubi, Shahab Shahabi, Saba Sheikhbahaei, Amir Hossein Davarpanah Jazi

Abstract readEvaluation Study
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In one paragraph

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 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Large language models in obesity: a systematic review.International journal of obesity (2005) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mohammad MahjoubiMinimally Invasive Surgery Research Center, Iran University of Medical Sciences, Tehran, Iran.
Shahab ShahabiMinimally Invasive Surgery Research Center, Iran University of Medical Sciences, Tehran, Iran.
Saba SheikhbahaeiHunter New England Local Health District, Newcastle, Australia.
Amir Hossein Davarpanah JaziMinimally Invasive Surgery Research Center, Iran University of Medical Sciences, Tehran, Iran. davarpanahjazi@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the rise of artificial intelligence (AI) in medical education, tools like OpenAI's ChatGPT-4 and DALL·E 3 have potential applications in enhancing learning materials. This study aims to evaluate ChatGPT-4o's proficiency in recognizing bariatric surgical procedures from illustrations and assess DALL·E 3's effectiveness in generating accurate surgical illustrations.

methodsIllustrations of six bariatric surgical procedures (One Anastomosis Gastric Bypass, Roux-en-Y Gastric Bypass, Single Anastomosis Duodeno-Ileal Bypass with Sleeve Gastrectomy, Sleeve Gastrectomy, Biliopancreatic Diversion, and Adjustable Gastric Banding) were sourced from the IFSO Atlas of Metabolic and Bariatric Surgery. ChatGPT-4 was tasked with identifying each procedure based on these illustrations to evaluate its classification accuracy. Simultaneously, DALL·E 3 was prompted with the specific names of each procedure to generate corresponding medical illustrations.

resultsChatGPT-4 correctly identified only the Adjustable Gastric Banding illustration, misclassifying the other five procedures. DALL·E 3 failed to produce accurate illustrations for all six procedures.

conclusionThe study underscores the need for further evaluation of AI in bariatric surgery. Both ChatGPT-4 and DALL·E 3, while promising, have significant limitations in recognizing and generating accurate illustrations of bariatric surgical procedures. These findings call for continued research and development to make AI models suitable for medical education applications in bariatric surgery.

Indexed as

Artificial IntelligenceBariatric SurgeryMedical IllustrationObesity, MorbidGenerative Artificial IntelligenceHumansBariatric surgeryChatGPTDALLEGenerative artificial intelligenceImage

Identifiers

PMID39733375

What OpenQuestion holds

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Registered trials

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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.