GuidelineThe Journal of pathology2019
Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.
Guideline in The Journal of pathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 190 papers, 1 of them a synthesis that pooled 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.
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
190 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence-Assisted Histopathologic Diagnosis and Grading of Oral Epithelial Dysplasia: A Systematic Review and Functional Meta-synthesis.Head and neck pathology · 2026Pooled it
- Next-generation kidney tissue analysis - spatial omics and digital pathology.Nature reviews. Nephrology · 2026Review
- Agentic systems in computational pathology: architectures, evidence, and translational challenges.Journal of translational medicine · 2026Review
- Artificial Intelligence and Digital Pathology: Technological Transformation and Strategic Impact in Clinical Research and Medical Affairs.Life (Basel, Switzerland) · 2026Review
- Regulatory science for AI-basedJournal of pathology informatics · 2026Article
- REMIL-IBD: Region-filtered multiple instance learning for interpretable slide-level grading of inflammatory bowel disease.Journal of pathology informatics · 2026Article
- Rethinking pathology image analysis through shuffling.npj biomedical innovations · 2026Article
- Application and exploration of digital pathology technology in standardized residency training.BMC medical education · 2026Article
- Compositional and interpretable representation of histology using AI foundation models and sparse autoencoders.bioRxiv : the preprint server for biology · 2026Article
- Universal and transferable attacks on pathology foundation models using microscopic perturbations.Light, science & applications · 2026Article
- Explainable artificial intelligence with pyramid vision transformer model for multi-class malignant cell classification on cytology slides.Scientific reports · 2026Article
- What's new in digital and computational pathology 2026: advances in adoption, standards, AI technologies, and clinical integration.Journal of pathology and translational medicine · 2026Article
- Assessing postoperative pancreatic fistula risk: from subjective assessment to digital pathology-assisted quantitative precision.Gland surgery · 2026Article
- AI caption generation model for digital pathology of adenocarcinoma in endoscopic histopathology using multi-instance attention mechanisms.Scientific reports · 2026Article
- Automatic clear cell renal cell carcinoma grading framework using histopathological images via artificial intelligence: a benchmarking study.BioData mining · 2026Article
- DenseUNet for Breast Cancer Segmentation in Histopathological Images.Journal of medical signals and sensors · 2026Article
- Pediatric brain tumor classification using digital pathology and deep learning: Evaluation of SOTA methods on a multi-center Swedish cohort.Brain pathology (Zurich, Switzerland) · 2026Article
- ADPv2: A hierarchical histological tissue type-annotated dataset for potential biomarker discovery of colorectal disease.Journal of pathology informatics · 2026Article
- Digital pathology and artificial intelligence in breast and gynecologic oncology: from molecular prediction to multimodal integration.Frontiers in oncology · 2026Review
- Digital pathology imaging artificial intelligence in cancer research and clinical trials: An NCI workshop report.Journal of pathology informatics · 2026Review
130 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review offers a historical perspective and describes the potential clinical benefits from research and applications in this field, as well as significant obstacles to adoption. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber-security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
Indexed as
Identifiers
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.