Evidence map›Paper›PMID 39592492›Full record

ArticleAesthetic plastic surgery2025

Performance of Artificial Intelligence Chatbots in Answering Clinical Questions on Japanese Practical Guidelines for Implant-based Breast Reconstruction.

Makoto Shiraishi, Yoshihiro Sowa, Koichi Tomita, Yasunobu Terao, Toshihiko Satake, Mayu Muto, Yuhei Morita, Shino Higai, Yoshihiro Toyohara, Yasue Kurokawa and 2 more

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Article in Aesthetic plastic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Performance of AI Chatbots in Preliminary Diagnosis of Maxillofacial Pathologies.Medical science monitor : international medical journal of experimental and clinical research · 2025
    Article
  8. Article
  9. Article
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

12 authors.

Makoto ShiraishiDepartment of Plastic and Reconstructive Surgery, The University of Tokyo Hospital, Tokyo, Japan.ORCID 0000-0002-3734-2085
Yoshihiro SowaDepartment of Plastic Surgery, Jichi Medical University, Yakushiji, Shimotsuke, Tochigi, Japan. ysowawan@gmail.com.ORCID 0000-0002-7112-1630
Koichi TomitaDepartment of Plastic and Reconstructive Surgery, Kindai University, Osaka, Japan.
Yasunobu TeraoDepartment of Plastic and Reconstructive Surgery, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan.
Toshihiko SatakeDepartment of Plastic, Reconstructive and Aesthetic Surgery, Toyama University Hospital, Toyama, Japan.
Mayu MutoDepartment of Plastic, Reconstructive and Aesthetic Surgery, Toyama University Hospital, Toyama, Japan.
Yuhei MoritaDepartment of Plastic Surgery, Jichi Medical University, Yakushiji, Shimotsuke, Tochigi, Japan.
Shino HigaiDepartment of Plastic Surgery, Jichi Medical University, Yakushiji, Shimotsuke, Tochigi, Japan.
Yoshihiro ToyoharaDepartment of Plastic Surgery, Jichi Medical University, Yakushiji, Shimotsuke, Tochigi, Japan.
Yasue KurokawaDepartment of Plastic Surgery, Jichi Medical University, Yakushiji, Shimotsuke, Tochigi, Japan.
Ataru SunagaDepartment of Plastic Surgery, Jichi Medical University, Yakushiji, Shimotsuke, Tochigi, Japan.
Mutsumi OkazakiDepartment of Plastic and Reconstructive Surgery, The University of Tokyo Hospital, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) chatbots, including ChatGPT-4 (GPT-4) and Grok-1 (Grok), have been shown to be potentially useful in several medical fields, but have not been examined in plastic and aesthetic surgery. The aim of this study is to evaluate the responses of these AI chatbots for clinical questions (CQs) related to the guidelines for implant-based breast reconstruction (IBBR) published by the Japan Society of Plastic and Reconstructive Surgery (JSPRS) in 2021.

methodsCQs in the JSPRS guidelines were used as question sources. Responses from two AI chatbots, GPT-4 and Grok, were evaluated for accuracy, informativeness, and readability by five Japanese Board-certified breast reconstruction specialists and five Japanese clinical fellows of plastic surgery.

resultsGPT-4 outperformed Grok significantly in terms of accuracy (p < 0.001), informativeness (p < 0.001), and readability (p < 0.001) when evaluated by plastic surgery fellows. Compared to the original guidelines, Grok scored significantly lower in all three areas (all p < 0.001). The accuracy of GPT-4 was rated to be significantly higher based on scores given by plastic surgery fellows compared to those of breast reconstruction specialists (p = 0.012), whereas there was no significant difference between these scores for Grok.

conclusionsThe study suggests that GPT-4 has the potential to assist in interpreting and applying clinical guidelines for IBBR but importantly there is still a risk that AI chatbots can misinform. Further studies are needed to understand the broader role of current and future AI chatbots in breast reconstruction surgery. 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 Table of Contents or online Instructions to Authors www.springer.com/00266 .

Indexed as

Artificial IntelligenceBreast ImplantationBreast ImplantsMammaplastyPractice Guidelines as TopicBreast NeoplasmsEast Asian PeopleFemaleGenerative Artificial IntelligenceHumansJapanSurveys and QuestionnairesArtificial intelligenceBreast implantBreast reconstructionChatGPTGrok

Identifiers

PMID39592492

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.