Evidence map›Paper›PMID 42549539›Full record

ReviewJournal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG2026

Digital Pathology in Dermatology - Current Status, Applications and Perspectives.

Cornelia S L Müller, Torsten Hansen

Abstract readReview
In one paragraph

Review in Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG, 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

2 authors.

Cornelia S L MüllerMedical Service Center for Histology, Cytology and Molecular Pathology Trier, Germany.
Torsten HansenMedical Service Center for Histology, Cytology and Molecular Pathology Trier, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital pathology has become an increasingly established component of routine diagnostic practice in recent years. Whole-slide imaging enables the complete digitization of histological slides and allows for primary diagnosis using digital images. This development offers new opportunities for diagnostics, consultations, archiving, education, and quality assurance. In dermatology and dermatopathology, digital pathology is particularly relevant for the evaluation of inflammatory skin diseases, melanocytic lesions, epithelial skin tumors, and immunohistochemical analyses. This article provides an overview of the technical principles of digital pathology, describes workflow integration and implementation in clinical routine, and outlines requirements for quality assurance and validation. Key applications in dermatology as well as advantages and limitations of digital diagnosis are discussed. A dedicated section addresses the role of artificial intelligence as an assistive tool in dermatopathological diagnostics. The aim of this CME article is to provide dermatologists and pathologists with a comprehensive basis for evaluating and applying digital pathology systems in clinical practice and to place current developments into a realistic clinical context.

Indexed as

DermatologyImage Interpretation, Computer-AssistedSkin DiseasesArtificial IntelligenceDigital HealthHumansSkin NeoplasmsTelepathologyArtificial intelligenceDermatopathologyDigital pathologyQuality assuranceTelepathologyWhole‐slide imaging

Identifiers

PMID42549539
PMCPMC13435137

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.