ReviewLaboratory investigation; a journal of technical methods and pathology2021
Artificial intelligence and computational pathology.
Review in Laboratory investigation; a journal of technical methods and pathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 200 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
200 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP).Diagnostics (Basel, Switzerland) · 2021Guideline
- GrandQC adaptation as an artificial intelligence tool for quantitative artifact detection in hematoxylin and eosin whole-slide images-Simulation of quality control biopsies day.Journal of pathology informatics · 2026Article
- Benefits of high-magnification and color information in computational pathology-An exploratory review.Journal of pathology informatics · 2026Review
- Article
- Computational pathology model to predict recurrence-free survival in NMPUC patients on BCG-therapy.NPJ precision oncology · 2026Article
- Review
- Clinical artificial intelligence applications of vision-language foundation models.PLOS digital health · 2026Review
- Development and validation of artificial intelligence-based model for bladder cancer immunophenotyping using whole slide images.NPJ precision oncology · 2026Article
- Machine learning-based integration of transcriptome and digital pathology for predicting chemoresistance in muscle-invasive bladder cancer.Experimental & molecular medicine · 2026Article
- Survival risk prediction for patients with lung adenocarcinoma containing micropapillary components based on weakly supervised pathomics.Journal of thoracic disease · 2026Article
- Telepathology and Mobile Health System for Province-Wide Pathology Consultation in Henan, China: Retrospective Evaluation Study.Journal of medical Internet research · 2026Observational
- Polarimetric imaging of collagen in histopathology specimens: an investigation of congo red and picrosirius red-stained placenta and skin.Scientific reports · 2026Article
- Human versus artificial intelligence in oral pathology diagnosis: a comparative study of ChatGPT, Grok, and MANUS.Scientific reports · 2026Article
- Debating the pros and cons of computational pathology at the European Congress of Pathology (ECP) 2024.Virchows Archiv : an international journal of pathology · 2026Article
- Molecular Pathology of Cardiomyopathies: Bridging Morphology, Genomics, and Clinical Phenotypes.Current issues in molecular biology · 2026Review
- ADPv2: A hierarchical histological tissue type-annotated dataset for potential biomarker discovery of colorectal disease.Journal of pathology informatics · 2026Article
- Foundation models in computational pathology: methods, applications and clinical implications.BMJ oncology · 2026Review
- GICPIdb: an archival repository of multimodal data focusing on pathological images for gastrointestinal cancers.Frontiers in big data · 2026Article
- AI-driven multi-omics integration in breast cancer: clinical applications, immunotherapy prediction, and translational challenges.Frontiers in molecular biosciences · 2026Review
- Foundation Models in Cancer Pathology: Techniques, Applications, and Future Directions.Research (Washington, D.C.) · 2026Review
140 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
Data processing and learning has become a spearhead for the advancement of medicine, with pathology and laboratory medicine has no exception. The incorporation of scientific research through clinical informatics, including genomics, proteomics, bioinformatics, and biostatistics, into clinical practice unlocks innovative approaches for patient care. Computational pathology is burgeoning subspecialty in pathology that promises a better-integrated solution to whole-slide images, multi-omics data, and clinical informatics. However, computational pathology faces several challenges, including the ability to integrate raw data from different sources, limitation of hardware processing capacity, and a lack of specific training programs, as well as issues on ethics and larger societal acceptable practices that are still solidifying. The establishment of the entire industry of computational pathology requires far-reaching changes of the three essential elements connecting patients and doctors: the local laboratory, the scan center, and the central cloud hub/portal for data processing and retrieval. Computational pathology, unlocked through information integration and advanced digital communication networks, has the potential to improve clinical workflow efficiency, diagnostic quality, and ultimately create personalized diagnosis and treatment plans for patients. This review describes clinical perspectives and discusses the statistical methods, clinical applications, potential obstacles, and future directions of computational pathology.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.