Evidence map›Paper›PMID 39860006›Full record

ArticleLife (Basel, Switzerland)2025

Pilot Study on AI Image Analysis for Lower-Limb Reconstruction-Assessing ChatGPT-4's Recommendations in Comparison to Board-Certified Plastic Surgeons and Resident Physicians.

Silke Graul, Michael A Pais, Rafael Loucas, Tobias Rohrbach, Elias Volkmer, Sebastian Leitsch, Thomas Holzbach

Abstract read
In one paragraph

Article in Life (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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

7 authors.

Silke GraulDepartment of Hand and Plastic Surgery, Thurgau Hospital Group, 8501 Frauenfeld, Switzerland.
Michael A PaisDepartment of Hand and Plastic Surgery, Thurgau Hospital Group, 8501 Frauenfeld, Switzerland.
Rafael LoucasDepartment of Plastic, Hand and Reconstructive Surgery, University Hospital Regensburg, 93053 Regensburg, Germany.
Tobias RohrbachAustralian Centre of Health Engagement, Evidence and Values (ACHEEV), University of Wollongong, Wollongong 2500, Australia.
Elias VolkmerDepartment of Hand Surgery, Helios Klinikum Munich West, 81241 Munich, Germany.
Sebastian LeitschDepartment of Hand and Plastic Surgery, Thurgau Hospital Group, 8501 Frauenfeld, Switzerland.
Thomas HolzbachDepartment of Hand and Plastic Surgery, Thurgau Hospital Group, 8501 Frauenfeld, Switzerland.ORCID 0000-0003-2324-9813

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AI, especially ChatGPT, is impacting healthcare through applications in research, patient communication, and training. To our knowledge, this is the first study to examine ChatGPT-4's ability to analyze images of lower leg defects and assesses its understanding of complex case reports in comparison to the performance of board-certified surgeons and residents. We conducted a cross-sectional survey in Switzerland, Germany, and Austria, where 52 participants reviewed images depicting lower leg defects within fictitious patient profiles and selected the optimal reconstruction techniques. The questionnaire included cases with varied difficulty, and answer options did not always include the most obvious choices. Findings highlight that ChatGPT-4 successfully evaluated various reconstruction methods but struggled to determine the optimal solution based on the available information in visual and written forms. A chi-squared test of independence was performed to investigate the overall association between answer options (A, B, C, and D) and rater group (board-certified surgeons, ChatGPT-4, and resident). Inter-group rater associations showed significant overall test results (

Indexed as

AIartificial intelligenceChatGPTChatGPT-4image analysislower-limb reconstructionplastic surgeryreconstructive surgerysurvey

Identifiers

PMID39860006
PMCPMC11766909

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.