Evidence map›Paper›PMID 41102487›Full record

ReviewVirchows Archiv : an international journal of pathology2026

Practical consequences of the European union-AI act for anatomic pathology laboratories a European society of pathology and European society of digital and integrative pathology commissioned expert opinion paper.

Frederik Deman, Sofia Palmieri, Glenn Broeckx, Thomas Van Den Berghe, Inti Zlobec, Peter Schirmacher, Sara P Oliveira, Luca Di Tommaso, Norman Zerbe, Vincenzo L'Imperio and 5 more

Abstract readReview
In one paragraph

Review in Virchows Archiv : an international journal of pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. The patient matters: a roundtable discussion on pathology in the era of digitization and AI.Virchows Archiv : an international journal of pathology · 2026
    Article
  4. Review
  5. Article
  6. 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

15 authors.

Frederik Deman *PA2, Dept. of Pathology, Ziekenhuis aan de Stroom (ZAS), Antwerp, Belgium. Frederik.deman@zas.be.ORCID http://orcid.org/0000-0002-6925-571X
Sofia Palmieri *Metamedica, University of Ghent, Ghent, Belgium.
Glenn BroeckxPA2, Dept. of Pathology, Ziekenhuis aan de Stroom (ZAS), Antwerp, Belgium.
Thomas Van Den BergheDepartment of Diagnostic Sciences, Faculty of Medicine and Health Sciences, University of Ghent, Ghent, Belgium.
Inti ZlobecFaculty of Medicine, Department Digital Medicine, University of Bern, Bern, Switzerland.
Peter SchirmacherInstitute of Pathology Heidelberg, Heidelberg University, Heidelberg, Germany.
Sara P OliveiraComputational Pathology Group, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Luca Di TommasoPathology Unit, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy.
Norman ZerbeInstitute of Pathology, RWTH Aachen University Hospital, Aachen, Germany.
Vincenzo L'ImperioSchool of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.
Sabine DeclercqPA2, Dept. of Pathology, Ziekenhuis aan de Stroom (ZAS), Antwerp, Belgium.
Marc Van Den BulckeBelgian Cancer Centre, Sciensano, Brussels, Belgium.
Anouk WaeytensBelgian Cancer Centre, Sciensano, Brussels, Belgium.
Roberto SalgadoPA2, Dept. of Pathology, Ziekenhuis aan de Stroom (ZAS), Antwerp, Belgium.
Amélie DendoovenDepartment of Diagnostic Sciences, Faculty of Medicine and Health Sciences, University of Ghent, Ghent, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The European Union Artificial Intelligence Act (AI Act) introduces a landmark regulatory framework governing the development, deployment, and post-marketing requirements and maintenance of AI systems, with growing relevance for the field of digital pathology. This paper explores the practical implications of the AI Act for pathology laboratories, particularly in relation to high-risk AI tools used in diagnostic workflows. We outline the Act's risk-based classification approach and highlight key obligations for both AI developers and users, including requirements for transparency, explainability, risk management, data governance, human oversight, and staff training. Special attention is given to how these regulatory demands relate to existing healthcare standards and implemented quality systems in anatomic pathology laboratories. By translating the AI Act's legal language into concrete, pathology-specific recommendations, this work provides guidance supporting safe and effective AI integration in clinical practice. While the legislation introduces operational and administrative challenges, it also presents an opportunity to enhance accountability, trust, and innovation in pathology. This paper aims to equip anatomic pathology laboratories with the tools and insights needed to responsibly navigate the evolving regulatory landscape of AI in healthcare.

Indexed as

Artificial IntelligencePathology, ClinicalEuropean UnionHumansAIGuidanceLegislationPathology

Identifiers

PMID41102487
PMCPMC13053491

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.