Evidence map›Paper›PMID 41680309›Full record

ArticleAesthetic plastic surgery2026

Assessing ChatGPT-4o's Image Generation for Educational Infographics in Plastic Surgery: A Pilot Study.

Gianluca Marcaccini, Omar Shadid, Ishith Seth, Elena Bagalà, Roberto Cuomo, Warren M Rozen

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Article in Aesthetic plastic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Gianluca MarcacciniDepartment of Plastic and Reconstructive Surgery, University of Siena, 53100, Siena, Italy. gianlu32@gmail.com.ORCID http://orcid.org/0000-0002-8621-8216
Omar ShadidDepartment of Plastic and Reconstructive Surgery, Frankston Hospital, Peninsula Health, Frankston, Victoria, Australia.
Ishith SethDepartment of Plastic and Reconstructive Surgery, Frankston Hospital, Peninsula Health, Frankston, Victoria, Australia.
Elena BagalàDepartment of Plastic and Reconstructive Surgery, University of Siena, 53100, Siena, Italy.
Roberto CuomoDepartment of Plastic and Reconstructive Surgery, University of Siena, 53100, Siena, Italy.
Warren M RozenDepartment of Plastic and Reconstructive Surgery, Frankston Hospital, Peninsula Health, Frankston, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntegrating generative artificial intelligence (AI) in patient education has opened new avenues for creating engaging and informative content, especially in visually intensive specialties such as plastic surgery. ChatGPT-4o, developed by OpenAI, incorporates image generation capabilities alongside advanced language processing, offering the potential for rapid development of illustrated educational tools tailored to patient needs.

methodsThis pilot study explored the efficacy of ChatGPT-4o in generating educational infographics for five commonly performed plastic surgery procedures: rhinoplasty, blepharoplasty, abdominoplasty, facelift, and liposuction. For each procedure, structured prompts were used to create infographics that combined explanatory text with detailed visuals. The outputs were evaluated by a panel of expert plastic surgeons (N = 4) across five domains: visual appeal, clarity of information, anatomical accuracy, educational value, and overall suitability for patient education. Evaluation scores were analyzed using descriptive statistics and one-sample t tests.

resultsAll infographics received mean Likert scores exceeding 4.0 in each domain, with visual appeal rated highest (mean 4.72 ± 0.08) and anatomical accuracy comparatively lower (mean 4.32 ± 0.08). Statistical analysis confirmed that the differences from the benchmark of 4.0 were significant in all domains (p < 0.001), supporting the model's effectiveness. As no real patient data or identifiable information was used, the study was conducted in accordance with the Declaration of Helsinki, and no institutional ethics review was required.

conclusionChatGPT-4o demonstrates strong potential as a tool for generating educationally effective and visually appealing infographics for patient education in plastic surgery. While further refinement is needed to improve anatomical precision, these findings support broader integration of AI-generated visual tools into clinical practice, with implications for improving patient communication, engagement, and informed consent. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Indexed as

Patient Education as TopicPlastic Surgery ProceduresSurgery, PlasticFemaleGenerative Artificial IntelligenceHumansInfographics as TopicMalePilot ProjectsChatGPT-4oGenerative AIMedical infographicPatient educationPlastic surgery

Identifiers

PMID41680309

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.