ReviewNPJ digital medicine2025
H&E to IHC virtual staining methods in breast cancer: an overview and benchmarking.
Review in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- Tumor-Aware Unsupervised Digital HER2 Immunohistochemistry via Dual Contrastive Learning.Biosensors · 2026Article
- Artificial Intelligence for Diagnostic and Prognostic Support in Breast Cancer: A Literature Overview.Cancers · 2026Review
- HER2 Score-Aware Virtual Immunohistochemistry via Non-Contrastive Multi-Task Translation.Diagnostics (Basel, Switzerland) · 2026Article
- Virtual multiplex staining of the pancreatic islets across type 1 diabetes progression using a Schrödinger bridge.bioRxiv : the preprint server for biology · 2026Article
- Deep learning-driven recognition of panoramic tumor microenvironment features in H&E sections and its application.Journal for immunotherapy of cancer · 2026Review
- Attention-guided and MIL-constrained CycleGAN for high-fidelity virtual p16 and Ki-67 staining.Frontiers in medical technology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Immunohistochemistry (IHC) is crucial for the clinical categorisation of breast cancer cases. Deep generative models may offer a cost-effective alternative by virtually generating IHC images from hematoxylin and eosin samples. This review explores the state-of-the-art in virtual staining for breast cancer biomarkers (HER2, PgR, ER and Ki-67) and benchmarks several models on public datasets. It serves as a resource for researchers and clinicians interested in applying or developing virtual staining techniques.
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.