ReviewJournal of the American Medical Informatics Association : JAMIA
Pathology imaging informatics for quantitative analysis of whole-slide images.
Review in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 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
114 citing papers in PubMed, 1 synthesis or guideline pooled it, 255 citations in OpenAlex.
- Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists.Archives of pathology & laboratory medicine · 2019Guideline
- B-cell and T-cell quantification in minor salivary glands in primary Sjögren's syndrome: development and validation of a pixel-based digital procedure.Arthritis research & therapy · 2016Trial
- Evaluation of the Usefulness of Machine Learning and Artificial Intelligence on Hyperspectral Images in the Diagnosis of Myelodysplastic Syndrome.Journal of biophotonics · 2026Article
- Telepathology and Mobile Health System for Province-Wide Pathology Consultation in Henan, China: Retrospective Evaluation Study.Journal of medical Internet research · 2026Observational
- Artificial intelligence for triple-negative breast cancer from imaging to multi-omics.Frontiers in oncology · 2026Review
- Generative AI in lung adenocarcinoma pathology: methodological and interpretive considerations.International journal of surgery (London, England) · 2026Article
- NEUSEG: INTERPRETABLE UNSUPERVISED GM/WM SEGMENTATION IN BRAIN HISTOPATHOLOGY USING NUCLEI MORPHOMETRICS.Proceedings. IEEE International Symposium on Biomedical Imaging · 2026Article
- Visual analysis of research hot topics and trends of clinical decision support system based on CiteSpace.Langenbeck's archives of surgery · 2025Review
- Multimodal Integration Enhances Tissue Image Information Content: A Deep Feature Perspective.Bioengineering (Basel, Switzerland) · 2025Article
- Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Enhancing basal cell carcinoma classification in preoperative biopsies via transfer learning with weakly supervised graph transformers.BMC medical imaging · 2025Article
- PySpatial: A High-Speed Whole Slide Image Pathomics Toolkit.IS&T International Symposium on Electronic Imaging · 2025Article
- Utilizing a Pathomics Biomarker to Predict the Effectiveness of Bevacizumab in Ovarian Cancer Treatment.Bioengineering (Basel, Switzerland) · 2024Article
- High-performance Data Management for Whole Slide Image Analysis in Digital Pathology.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Article
- A multiscale model of the role of microenvironmental factors in cell segregation and heterogeneity in breast cancer development.PLoS computational biology · 2023Article
- Quantitative analysis of prion disease using an AI-powered digital pathology framework.Scientific reports · 2023Article
- Article
- A Novel Hybrid Approach for Classifying Osteosarcoma Using Deep Feature Extraction and Multilayer Perceptron.Diagnostics (Basel, Switzerland) · 2023Article
- An Accelerated Pipeline for Multi-label Renal Pathology Image Segmentation at the Whole Slide Image Level.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
54 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
4 authors at 1 institution in 1 country.
Funding
Abstract
objectivesWith the objective of bringing clinical decision support systems to reality, this article reviews histopathological whole-slide imaging informatics methods, associated challenges, and future research opportunities. TARGET AUDIENCE: This review targets pathologists and informaticians who have a limited understanding of the key aspects of whole-slide image (WSI) analysis and/or a limited knowledge of state-of-the-art technologies and analysis methods. SCOPE: First, we discuss the importance of imaging informatics in pathology and highlight the challenges posed by histopathological WSI. Next, we provide a thorough review of current methods for: quality control of histopathological images; feature extraction that captures image properties at the pixel, object, and semantic levels; predictive modeling that utilizes image features for diagnostic or prognostic applications; and data and information visualization that explores WSI for de novo discovery. In addition, we highlight future research directions and discuss the impact of large public repositories of histopathological data, such as the Cancer Genome Atlas, on the field of pathology informatics. Following the review, we present a case study to illustrate a clinical decision support system that begins with quality control and ends with predictive modeling for several cancer endpoints. Currently, state-of-the-art software tools only provide limited image processing capabilities instead of complete data analysis for clinical decision-making. We aim to inspire researchers to conduct more research in pathology imaging informatics so that clinical decision support can become a reality.
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.