Evidence map›Paper›PMID 40564849›Full record

ReviewDiagnostics (Basel, Switzerland)2025

The Role of ChatGPT in Dermatology Diagnostics.

Ziad Khamaysi, Mahdi Awwad, Badea Jiryis, Naji Bathish, Jonathan Shapiro

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
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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.

Ziad KhamaysiDepartment of Dermatology, Rambam Health Care Campus, Haifa 3109601, Israel.ORCID 0000-0001-9586-2807
Mahdi AwwadOphthalmology Unit, Tzafon Medical Center, Tiberias 1528001, Israel.
Badea JiryisDepartment of Dermatology, Rambam Health Care Campus, Haifa 3109601, Israel.
Naji BathishDermatology Unit, Ziv Medical Center, Safed 13100, Israel.
Jonathan ShapiroMaccabi Healthcare Services, Tel Aviv 6817110, Israel.ORCID 0000-0002-5154-7984

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI), especially large language models (LLMs) like ChatGPT, has disrupted different medical disciplines, including dermatology. This review explores the application of ChatGPT in dermatological diagnosis, emphasizing its role in natural language processing (NLP) for clinical data interpretation, differential diagnosis assistance, and patient communication enhancement. ChatGPT can enhance a diagnostic workflow when paired with image analysis tools, such as convolutional neural networks (CNNs), by merging text and image data. While it boasts great capabilities, it still faces some issues, such as its inability to perform any direct image analyses and the risk of inaccurate suggestions. Ethical considerations, including patient data privacy and the responsibilities of the clinician, are discussed. Future perspectives include an integrated multimodal model and AI-assisted framework for diagnosis, which shall improve dermatology practice.

Indexed as

ChatGPTdermatologydiagnosing

Identifiers

PMID40564849
PMCPMC12191462

What OpenQuestion holds

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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.