ArticleCureus2024
Assessing ChatGPT's Reliability as an Educational Resource for Information on Breast Reduction Surgery.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Assessing ChatGPT and Gemini Responses to Common Patient Questions Regarding Augmentation Mammaplasty.Aesthetic plastic surgery · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionWith advances in AI and machine learning, platforms like OpenAI's ChatGPT are emerging as educational resources. While these platforms offer easy access and user-friendliness due to their personalized conversational responses, concerns about the accuracy and reliability of their information persist. As one of the most common surgical procedures performed by plastic surgeons worldwide, breast reduction surgery (BRS) offers relief for the physical and emotional burdens of large breasts. However, like any surgical procedure, it can raise a multitude of questions and anxiety.
methodsTo evaluate the quality of medical information provided by ChatGPT in response to common patient inquiries about breast reduction surgery, we developed a 15-question questionnaire with typical patient questions about BRS. These questions were presented to ChatGPT, and the answers were compiled and presented to five board-certified plastic surgeons. Each specialist categorized the response as (1) Appropriate, the response accurately reflects current medical knowledge and best practices for BRS; (2) No, not thorough, the response lacks sufficient detail to be a helpful educational resource; (3) No, inaccurate, the response contains misleading or incorrect information.
resultsA total of 75 survey responses were obtained, with five experts each analyzing 15 answers from ChatGPT. Of these, 69 (92%) responses were determined to be accurate. However, six (8%) responses were concerning to our experts: four (5.3%) lacked detail, and two (2.7%) were found to be inaccurate. Chi-square analysis revealed no statistical significance in the distribution of responses categorized as "accurate" versus "not thorough/inaccurate," and "not thorough" versus "inaccurate" (p=0.778 and p=0.306, respectively).
conclusionWhile ChatGPT can provide patients with basic background knowledge on BRS and empower patients to ask more informed questions during consultations, it should not replace the consultation and expert guidance of a board-certified plastic surgeon.
Indexed as
Identifiers
What OpenQuestion holds
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.