ReviewJournal of pathology informatics2018
Artificial Intelligence and Digital Pathology: Challenges and Opportunities.
Review in Journal of pathology informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 199 papers, 4 of them syntheses 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
199 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Digital pathology in forensic science: a systematic review of the literature.Forensic science, medicine, and pathology · 2026Pooled it
- Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2022Pooled it
- Ethics of AI in Radiology: A Review of Ethical and Societal Implications.Frontiers in big data · 2022Pooled it
- Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.The Journal of pathology · 2019Guideline
- An interpretable deep learning framework for multiclass bone marrow cytomorphology classification using EfficientNet and post hoc visualization techniques.Journal of pathology informatics · 2026Article
- Artificial intelligence in digital pathology diagnosis and analysis: Technologies, clinical integration, and future prospects (Review).Biomedical reports · 2026Review
- AI In Leukemia Diagnostics: Complementing the Pathologist's Role.International journal of laboratory hematology · 2026Review
- Artificial Intelligence and Digital Pathology: Technological Transformation and Strategic Impact in Clinical Research and Medical Affairs.Life (Basel, Switzerland) · 2026Review
- Comprehensive molecular profiling of combined hepatocellular carcinoma and cholangiocarcinoma reveals distinct Notch signaling subgroups with prognostic significance.Virchows Archiv : an international journal of pathology · 2026Article
- Deep-Learning Solution Providing Molecular Marker Subtyping of Breast Cancer Whole Slide Images: Protocol for a UK Clinical Service Evaluation Study.JMIR research protocols · 2026Article
- Artificial Intelligence in Dermatopathology: An Update and Review of the Current Literature.Diagnostics (Basel, Switzerland) · 2026Review
- PATHOS: Pathology attention framework for treatment response stratification in ovarian high-grade serous carcinomas following neoadjuvant chemotherapy on H&E images.Journal of pathology informatics · 2026Article
- Mapping the Road Ahead: A Collective Journey in Artificial Intelligence for Health and Medicine.Diagnostics (Basel, Switzerland) · 2026Article
- Transforming Gastric Biopsy Diagnostics: Integrating Omics Technologies and Artificial Intelligence.Biomedicines · 2026Article
- Toward a regional digital pathology network in Tuscany: current status and implementation roadmap.Virchows Archiv : an international journal of pathology · 2026Article
- Pathobiological Dictionary Defining Pathomics and Texture Features: Addressing Understandable AI Issues in Personalized Liver Cancer; Dictionary Version LCP1.0.Journal of imaging informatics in medicine · 2026Article
- SHEST: single-cell-level artificial intelligence from haematoxylin and eosin morphology for cell-type prediction and spatial transcriptomics reconstruction.Briefings in bioinformatics · 2026Article
- An integrated system from microscopy to AI for real-time object detection in endometrial cytology.Journal of pathology informatics · 2026Article
- A Weakly Supervised Approach for HPV Status Prediction in Oropharyngeal Carcinoma from H&E-Stained Slides.Cancers · 2025Article
- Impact of the Genius Digital Diagnostics System on workflow and accuracy compared with the ThinPrep Imaging System for review of ThinPrep Papanicolaou tests.American journal of clinical pathology · 2025Article
139 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In light of the recent success of artificial intelligence (AI) in computer vision applications, many researchers and physicians expect that AI would be able to assist in many tasks in digital pathology. Although opportunities are both manifest and tangible, there are clearly many challenges that need to be overcome in order to exploit the AI potentials in computational pathology. In this paper, we strive to provide a realistic account of all challenges and opportunities of adopting AI algorithms in digital pathology from both engineering and pathology perspectives.
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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 OpenQuestion graph.