Evidence map›Paper›PMID 39507766›Full record

ArticleClinical, cosmetic and investigational dermatology2024

AI in Hidradenitis Suppurativa: Expert Evaluation of Patient-Facing Information.

Anne-Cécile Ezanno, Anne-Claire Fougerousse, Christelle Pruvost-Balland, François Maccari, Charlotte Fite, ResoVerneuil

Abstract read
In one paragraph

Article in Clinical, cosmetic and investigational dermatology, 2024. 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

6 authors.

Anne-Cécile EzannoDepartment of Digestive, Surgery, Begin Military Teaching Hospital, Saint Mandé, France.
Anne-Claire FougerousseDepartment of Dermatology, Begin Military Teaching Hospital, Saint Mandé, France.ORCID 0000-0002-2850-867X
Christelle Pruvost-BallandDepartment of Dermatology, University Hospital Pontchaillou, Rennes, France.
François MaccariDepartment of Dermatology, Begin Military Teaching Hospital, Saint Mandé and Medical Center, La Varenne Saint-Hilaire, France.
Charlotte FiteDepartment of Dermatology, Saint Joseph Hospital, Paris, France.
ResoVerneuil

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study investigates the accuracy of Artificial Intelligence (AI) chatbots, ChatGPT and Bard, in providing information on Hidradenitis Suppurativa (HS), aiming to explore their potential in assisting HS patients by offering insights into symptoms, thus possibly reducing the diagnostic and treatment time gap. Patients and Methods: Using questions formulated with the help of HS patient associations, both ChatGPT and Bard were assessed. Responses to these questions were evaluated by 18 hS experts. Results: ChatGPT's responses were considered accurate in 86% of cases, significantly outperforming Bard, which only achieved 14% accuracy. Despite the general efficacy of ChatGPT in providing relevant information across a range of HS-related queries, both AI systems showed limitations in offering adequate advice on treatments. The study identifies a significant difference in the performance of the two AIs, emphasizing the need for improvement in AI-driven medical advice, particularly regarding treatment options. Conclusion: The study highlights the potential of AI chatbots, particularly ChatGPT, in supporting HS patients by improving symptom understanding and potentially reducing the time to diagnosis and treatment. AI chatbots, while promising, cannot yet substitute for professional medical diagnosis and treatment, indicating the importance of enhancing AI capabilities for more accurate and reliable medical information dissemination.

Indexed as

acne inversaartificial intelligencedermatologyhidradenitis suppurativa

Identifiers

PMID39507766
PMCPMC11539865

What OpenQuestion holds

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LicenceCC BY-NC
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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.