Evidence map›Paper›PMID 41717521›Full record

ArticleTurkish journal of physical medicine and rehabilitation2025

Assessing the accuracy and reproducibility of artificial intelligence-generated medical responses by ChatGPT on Scheuermann's kyphosis.

Esra Giray, Özge Gülsüm Illeez, Merve Damla Korkmaz, Nalan Capan, Evrim Karadag Saygi, Resa Aydın

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Article in Turkish journal of physical medicine and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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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

6 authors.

Esra GirayDepartment of Physical Medicine and Rehabilitation, University of Health Sciences, Fatih Sultan Mehmet Training and Research Hospital, İstanbul, Türkiye.ORCID 0000-0003-3895-4486
Özge Gülsüm IlleezDepartment of Physical Medicine and Rehabilitation, University of Health Sciences, Fatih Sultan Mehmet Training and Research Hospital, İstanbul, Türkiye.ORCID 0000-0002-3824-4428
Merve Damla KorkmazDepartment of Physical Medicine and Rehabilitation, Biruni University Faculty of Medicine, İstanbul, Türkiye.ORCID 0000-0003-2422-5709
Nalan CapanDepartment of Physical Medicine and Rehabilitation, İstanbul University, İstanbul Faculty of Medicine, İstanbul, Türkiye.ORCID 0000-0002-9185-1809
Evrim Karadag SaygiDepartment of Physical Medicine and Rehabilitation, Marmara University School of Medicine, İstanbul, Türkiye.ORCID 0000-0002-7420-9902
Resa AydınDepartment of Physical Medicine and Rehabilitation, İstanbul University, İstanbul Faculty of Medicine, İstanbul, Türkiye.ORCID 0000-0002-8496-7424

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The study aimed to measure the performance and reproducibility of artificial intelligence in answering frequently asked questions about Scheuermann's kyphosis and to compare the artificial intelligence with the SOSORT (International Scientific Society on Scoliosis Orthopaedic and Rehabilitation Treatment) consensus in answering case-based questions. Materials and methods: In this cross-sectional study, 75 questions adapted from frequently asked questions about Scheuermann's kyphosis were queried twice on ChatGPT. Response similarity was assessed to investigate reproducibility. The accuracy of responses was scored based on a scale. Four case studies from the end of the 7 Results: ChatGPT provided correct and comprehensive answers to 43 (57.33%) questions, correct but not comprehensive answers to 29 (38.67%) questions, and partially incorrect answers to 3 (4%) questions. ChatGPT performed best in the quality-of-life category, with 18/19 (94.73%) correct scores (score of 1). ChatGPT performed worst in the diagnosis category, with 3/8 (37.5%) correct and comprehensive answers, and in the treatment and follow-up category, with 9/24 (37.5%) correct and comprehensive answers. ChatGPT provided reproducible answers to 92% of the questions. ChatGPT's responses to the treatment of all four case studies were incorrect. Conclusion: While ChatGPT can provide valuable general information regarding Scheuermann's kyphosis, its ability to offer accurate treatment-related advice is limited.

Indexed as

Artificial intelligenceChatGPTlarge language modelmachine learningScheuermann’s diseaseScheuermann’s kyphosis.

Identifiers

PMID41717521
PMCPMC12914328

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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.