ArticleJournal of pathology informatics2026
The critical role of standards for AI in digital pathology: Digital Pathology Association Concept Paper.
Article in Journal of pathology informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Agentic systems in computational pathology: architectures, evidence, and translational challenges.Journal of translational medicine · 2026Review
Corrections and comments
- Erratum issued
Authors and funding
21 authors.
Funding
Abstract
Background: The field of pathology has not yet fully realized the potential of artificial intelligence (AI) and digital pathology. Adoption must be driven by demonstrable utility, and successful implementation depends on interoperability and sustainability, which require established standards. We address the imminent challenges facing the field of AI in digital pathology, which currently suffers from a lack of coordinated and adopted standards. Methods: We conducted several roundtable discussions with key opinion leaders from multiple sectors across the healthcare ecosystem. Based on how standards are used, we distinguish different areas of practice (relevance, endorsement, and utility) and emphasize the importance of standards. Results: Our roundtable discussion centered on one key theme: successfully implementing AI in digital pathology depends on achieving a certain level of uniformity across practices. We derive an approach to describe the critical role of standards consisting of seven interdependent areas of practice: value recognition, existing standards, dependencies for AI, failures, management of standards, trends, and a roadmap for accelerated and sustainable adoption. The promise of standards and our approach can be understood as the interconnection of these areas. We address imminent challenges surrounding the field of digital pathology by providing an approach for interoperable, coordinated, and sustainable use of standards across diverse practice settings. Conclusion: With the concepts and frameworks outlined in this article, we highlight the importance of standards in pathology and their crucial role in driving computational advances and enabling AI solutions to enhance patient care.
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What Socratic holds
Registered trials
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.