Evidence map›Paper›PMID 41141910›Full record

ArticleFrontiers in artificial intelligence2025

When AI speaks like a specialist: ChatGPT-4 in the management of inflammatory bowel disease.

Elena De Cristofaro, Francesca Zorzi, Maria Abreu, Alice Colella, Giovanna Del Vecchio Blanco, Gionata Fiorino, Elisabetta Lolli, Nurulamin Noor, Loris Riccardo Lopetuso, Mathieu Pioche and 8 more

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 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. Review
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

18 authors.

Elena De CristofaroGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Francesca ZorziGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Maria AbreuDivision of Gastroenterology, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, United States.
Alice ColellaDepartment of Systems Medicine, University of Rome Tor Vergata, Rome, Italy.
Giovanna Del Vecchio BlancoGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Gionata FiorinoDepartment of Gastroenterology and Digestive Endoscopy, San Camillo-Forlanini Hospital, Rome, Italy.
Elisabetta LolliGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Nurulamin NoorDepartment of Gastroenterology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.
Loris Riccardo LopetusoMedicina interna e Gastroenterologia, CEMAD Centro Malattie dell'Apparato Digerente, Dipartimento di Scienze Mediche e Chirurgiche, Fondazione Policlinico Universitario Gemelli IRCSS, Rome, Italy.
Mathieu PiocheDepartment of Gastroenterology and Endoscopy, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France.
Jean GrimaldiDepartment of Gastroenterology and Endoscopy, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France.
Omero Alessandro PaoluziGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Joana RoseiraDepartment of Gastroenterology, Unidade Local de Saúde do Algarve, Portimão, Portugal.
Giorgia SenaGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Edoardo TronconeGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Emma CalabreseGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Giovanni MonteleoneGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.
Irene MarafiniGastroenterology Unit, Policlinico Universitario Tor Vergata, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) is gaining traction in healthcare, especially for patients' education. Inflammatory bowel diseases (IBD) require continuous engagement, yet the quality of online information accessed by patients is inconsistent. ChatGPT, a generative AI model, has shown promise in medical scenarios, but its role in IBD communication needs further evaluation. The objective of this study was to assess the quality of ChatGPT-4's responses to common patient questions about IBD, compared to those provided by experienced IBD specialists. Methods: Twenty-five frequently asked questions were collected during routine IBD outpatient visits and categorized into five themes: pregnancy/breastfeeding, diet, vaccinations, lifestyle, and medical therapy/surgery. Each question was answered by ChatGPT-4 and by two expert gastroenterologists. Responses were anonymized and evaluated by 12 physicians (six IBD experts and six non-experts) using a 5-point Likert scale across four dimensions: accuracy, reliability, comprehensibility, and actionability. Evaluators also attempted to identify whether responses were AI- or human-generated. Results: ChatGPT-4 responses received significantly higher overall scores than those from human experts (mean 4.28 vs. 4.05; Conclusion: ChatGPT-4 generated high-quality, clear, and actionable responses to IBD-related patient questions, often outperforming human experts. Its outputs were frequently indistinguishable from those written by physicians, suggesting potential as a supportive tool for patient education. Nonetheless, further studies are needed to assess real-world application and ensure appropriate use in personalized clinical care.

Indexed as

artificial inteligence (AI)CrohnIBDinflammationulcerative colitis

Identifiers

PMID41141910
PMCPMC12549657

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.