Back to search

Article

Hierarchically supervised computational pathology stratifies HER2 categories and ERBB2 amplification risk from routine H&E slides in breast cancer

2026-06-29

Abstract excerpt

<title>Abstract</title> <p> The equivocal human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) 2 + boundary remains a treatment-defining bottleneck in breast oncology because amplification adjudication requires resource-intensive in situ hybridisation/fluorescence in situ hybridisation (ISH/FISH) confirmation. This process is further constrained by turnaround time, manual signal interpretat...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
5ef0ad40-1124-5efc-adb0-f76c4b44c757
DOI
10.21203/rs.3.rs-10166827/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Hierarchically supervised computational pathology stratifies HER2 categories and ERBB2 amplification risk from routine H&amp;E slides in breast cancerDOI 10.21203/rs.3.rs-10166827/v1
Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy BenefitSemantic proximity
Predicting MammaPrint Recurrence Risk from Breast Cancer Pathological Images Using a Weakly Supervised TransformerSemantic proximity
Weak supervision of H&E slides reveals systems-level biology and functional states that govern therapeutic resistanceSemantic proximity
Multimodal histopathologic models stratify hormone receptor-positive early breast cancerSemantic proximity
DeepTRIAGE: Interpretable and Individualised Biomarker Scores using Attention Mechanism for the Classification of Breast Cancer Sub-typesSemantic proximity
Integration of Gene Expression and Digital Histology to Predict Treatment-Specific Responses in Breast CancerSemantic proximity
Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assaySemantic proximity
Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assaySemantic proximity
X-SPATIO: An Explanatory Deep Learning Pipeline for the Prediction and Visualization of Spatially Resolved Biomarker Expression in Triple-Negative Breast CancerSemantic proximity
Integrating Histology with Spatial Molecular Programs Using a Multimodal Foundation ModelSemantic proximity
Homologous recombination deficiency prediction from whole slide images using label refinement and foundation-model benchmarking in ovarian cancerSemantic proximity
Multiple instance learning on tile level-pathology images provides accurate and interpretable classification for breast cancer molecular subtypesSemantic proximity
Select a neighboring publication to make it the new centre.