Evidence map›Paper›PMID 41214495›Full record

ArticleBMC gastroenterology2025

Evaluation of the effectiveness of ChatGPT in supporting the management of autoimmune hepatitis effectiveness of ChatGPT in autoimmune hepatitis.

Muhammed Mustafa İnce, Ersan Özaslan

Abstract read
In one paragraph

Article in BMC gastroenterology, 2025. 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

2 authors.

Muhammed Mustafa İnceDepartment of Gastroenterology, University of Health Sciences, Ankara Bilkent City Hospital, Üniversiteler Mahallesi 1604. Cadde No: 9, Çankaya, Ankara, Turkey. drmustafaince@gmail.com.
Ersan ÖzaslanDepartment of Gastroenterology, University of Health Sciences, Ankara Bilkent City Hospital, Üniversiteler Mahallesi 1604. Cadde No: 9, Çankaya, Ankara, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimThis study aims to explore ChatGPT's ability to provide comprehensive information on AIH, its potential role in supporting the diagnostic and therapeutic processes for the disease and its broader implications for the use of artificial intelligence in healthcare. MATERIALS AND

methodsA total of 45 questions were designed and organized into 3 groups, each consisting of 15 questions (Group 1, Group 2, Group 3). The questions were categorized based on diffuculty, with Group 1 being the easiest and Group 3 the most challenging. Additionally, 5 case-based questions were formulated and ChatGPT was asked to provide diagnoses for these cases. All questions were re-asked after 14 days to evaluate the short-term stability and consistency of the artificial intelligence responses.

resultsThere was no statistically significant difference in the responses provided by ChatGPT initially (p = 0.328). However, when the questions were re-asked after 14 days, a significant difference was observed between the groups in terms of accuracy and completeness (p = 0.045 and p = 0.015, respectively). This difference was primarily due to the lower accuracy level in the responses for group 3 questions. Furthermore, when comparing ChatGPT's responses at 2-week intervals, a statistically significant improvement was noted, except for the completeness score of group 3 questions and the case-based questions.

conclusionOur findings suggest that ChatGPT may play a greater role in patient education and in supporting physicians in disease management. Future studies that test AI-generated responses from multiple perspectives and involve more centers could provide clearer guidance on this topic.

Indexed as

Artificial IntelligenceHepatitis, AutoimmuneFemaleGenerative Artificial IntelligenceHumansMaleSurveys and QuestionnairesArtificial intelligenceAutoimmune hepatitisChatGPT

Identifiers

PMID41214495
PMCPMC12599015

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.