Evidence map›Paper›PMID 42279570›Full record

ReviewDiagnostics (Basel, Switzerland)2026

Artificial Intelligence in Dermatopathology: An Update and Review of the Current Literature.

Ala' Abu-Dayeh, Gerardo Cazzato, Alessio Giubellino

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2026. 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

3 authors.

Ala' Abu-DayehDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55414, USA.ORCID 0000-0002-8728-7352
Gerardo CazzatoSection of Molecular Pathology, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari Aldo Moro, 70121 Bari, Italy.ORCID 0000-0003-0325-4316
Alessio GiubellinoDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55414, USA.ORCID 0000-0002-5352-0662

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) has pervaded many fields of medicine in the last few years on the wave of similar changes in other disciplines. Adoption of AI-driven technologies will progress in pathology in the years to come and will also transform our subspecialty of dermatopathology. From the adoption of AI in teaching to its use in clinical practice and in advancing our field through improved research capabilities, we expect a great deal of changes that will hopefully improve our assessment of tissue sections for several cutaneous pathologies. In this review, we offer an overview of where the use of these tools currently stands in dermatopathology and the potential directions that will transform the way we practice and do research. We cover AI's role in diagnosing various skin conditions, such as melanocytic lesions and other cutaneous skin cancers, and inflammatory dermatoses. The review further covers AI's contributions to workflow automation, like mitotic figure detection and counting, predictive analytics (e.g., melanoma prognosis), and educational tools (e.g., AI-driven simulators). It also addresses critical technical aspects, including data curation, algorithm development, and model validation. We aim to provide a comprehensive overview of how AI is transforming dermatopathology, from diagnosis and prognosis to education and clinical integration.

Indexed as

artificial intelligencedeep learningdermatopathologydigital pathologymachine learning

Identifiers

PMID42279570
PMCPMC13257086

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.