ReviewJournal of pathology informatics2024
On image search in histopathology.
Review in Journal of pathology informatics, 2024. 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 7 papers.
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
7 citing papers in PubMed.
- Towards robust foundation models for digital pathology.Nature communications · 2026Article
- mViSE: A visual search engine for analyzing multiplex IHC brain tissue images (spatial proteomics).Scientific reports · 2026Article
- MuCoSA: Multi-contextual similarity assessment for histopathology image search.Journal of pathology informatics · 2026Article
- Enhancing image retrieval through optimal barcode representation.Scientific reports · 2025Article
- Validation of histopathology foundation models through whole slide image retrieval.Scientific reports · 2025Article
- Multimodal learning for scalable representation of high-dimensional medical data.Frontiers in digital health · 2025Article
- Histopathology in focus: a review on explainable multi-modal approaches for breast cancer diagnosis.Frontiers in medicine · 2024Review
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pathology images of histopathology can be acquired from camera-mounted microscopes or whole-slide scanners. Utilizing similarity calculations to match patients based on these images holds significant potential in research and clinical contexts. Recent advancements in search technologies allow for implicit quantification of tissue morphology across diverse primary sites, facilitating comparisons, and enabling inferences about diagnosis, and potentially prognosis, and predictions for new patients when compared against a curated database of diagnosed and treated cases. In this article, we comprehensively review the latest developments in image search technologies for histopathology, offering a concise overview tailored for computational pathology researchers seeking effective, fast, and efficient image search methods in their work.
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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.