Evidence map›Paper›PMID 41262860›Full record

ArticlePostepy dermatologii i alergologii2025

Comparing physician and artificial intelligence ChatGPT-4 responses to common patient questions regarding hidradenitis suppurativa: a single-blind study.

Miłosz Lewandowski, Paweł Łukowicz, Dariusz Świetlik, Bożena Jendrysik, Wioletta Barańska-Rybak

Abstract read
In one paragraph

Article in Postepy dermatologii i alergologii, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers 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

5 authors.

Miłosz LewandowskiDepartment of Dermatology, Venereology and Allergology, Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland.
Paweł ŁukowiczDivision of Biostatistics and Neural Networks, Medical University of Gdansk, Gdansk, Poland.
Dariusz ŚwietlikDivision of Biostatistics and Neural Networks, Medical University of Gdansk, Gdansk, Poland.
Bożena JendrysikVeno-Med. Medical Centre, Lubliniec, Poland.
Wioletta Barańska-RybakDepartment of Dermatology, Venereology and Allergology, Faculty of Medicine, Medical University of Gdansk, Gdansk, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Artificial intelligence in medicine has increased enormously in recent years. Aim: To evaluate the effectiveness of ChatGPT-4 in answering common patient queries about hidradenitis suppurativa. Material and methods: A group of 31 physicians and 30 patients suffering from hidradenitis suppurativa independently evaluated and compared the quality, empathy, and satisfaction of the ChatGPT-4's and the dermatologist's responses to patient queries, in a single-blind study, without any information about answers' sources beforehand to minimize bias. Additionally, on the last page of the questionnaire, without the possibility of returning to assess the answers, the question was asked "Given that AI can answer your questions more accurately and empathetically than a doctor, who would you rather receive an answer from, the doctor or the AI". Results: For each variable, patients as well as medical doctors rated the answers generated by ChatGPT-4 significantly better than the answers provided by the dermatologist ( Conclusions: Our study revealed that despite ChatGPT-4's responses being rated better than the physician's, patients still prefer medical doctors as a source of information. Thus, AI will not replace physicians soon, although we should undoubtedly learn to live and cooperate with it.

Indexed as

artificial intelligenceChatGPTChatGPT-4dermatologyhidradenitis suppurativalarge language models

Identifiers

PMID41262860
PMCPMC12624385

What OpenQuestion holds

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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.