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References from Foundation Model-Based Computational Pathology Predicts Breast Cancer Biomarker Status from Intraoperative Frozen Sections. Local targets link to admitted publications; unresolved targets remain external evidence.
Breast cancer: pathogenesis and treatments
10.1038/s41392-024-02108-4 · 2025 · External reference
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10.1038/nature11412 · 2012 · External reference
Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013
10.1093/annonc/mdt303 · 2013 · External reference
HER2-targeting peptide drug conjugate with better penetrability for effective breast cancer therapy
10.15212/bioi-2023-0006 · 2023 · External reference
Human epidermal growth factor receptor 2 testing in breast cancer: ASCO-College of American Pathologists guideline update
10.1200/jco.22.02864 · 2023 · External reference
Speed meets precision: rapid intraoperative diagnostics in neuro-oncologic surgery
10.1016/j.trecan.2025.12.003 · 2026 · External reference
Application of intraoperative frozen section examination in the management of female breast cancer in China: a nationwide, multicenter 10-year epidemiological study
10.1186/1477-7819-12-225 · 2014 · External reference
Neural Network Based Classification of Breast Cancer Histopathological Image from Intraoperative Rapid Frozen Sections
10.1007/s10278-023-00802-3 · 2023 · External reference
Machine learning for cryosection pathology predicts the 2021 WHO classification of glioma
10.1016/j.medj.2023.06.002 · 2023 · External reference
Deep learning-based differentiation of benign and malignant thyroid follicular neoplasms on multiscale intraoperative frozen pathological images: A multicenter diagnostic study
10.21147/j.issn.1000-9604.2025.03.02 · 2025 · External reference
Molecular classification of breast cancer: what the pathologist needs to know
10.1016/j.pathol.2016.10.012 · 2017 · External reference
Intratumoral heterogeneity of Ki67 proliferation index outperforms conventional immunohistochemistry prognostic factors in estrogen receptor-positive HER2-negative breast cancer
10.1007/s00428-024-03737-4 · 2025 · External reference
Data-efficient and weakly supervised computational pathology on whole-slide images
10.1038/s41551-020-00682-w · 2021 · External reference
Towards a general-purpose foundation model for computational pathology
10.1038/s41591-024-02857-3 · 2024 · External reference
Virchow: a million-slide digital pathology foundation model
2023 · External reference
DINOv2: learning robust visual features without supervision
2023 · External reference
Unresolved reference
External reference
Virchow2: scaling self-supervised mixed magnification models in pathology
2024 · External reference
A whole-slide foundation model for digital pathology from real-world data
10.1038/s41586-024-07441-w · 2024 · External reference
SMOTE: synthetic minority over-sampling technique
10.1613/jair.953 · 2002 · External reference
10.1109/cvpr52733.2024.01078
10.1109/cvpr52733.2024.01078 · External reference
10.1109/cvpr52733.2024.01076
10.1109/cvpr52733.2024.01076 · External reference
TransMIL: transformer based correlated multiple instance learning for whole slide image classification
2021 · External reference
10.1007/978-3-031-73668-1_8
10.1007/978-3-031-73668-1_8 · External reference
Evolution of frozen section in carcinoma breast: systematic review
10.1155/2022/4958580 · 2022 · External reference
Weakly-supervised deep learning models enable HER2-low prediction from H&E-stained slides
10.1186/s13058-024-01863-0 · 2024 · External reference
Machine learning prediction of HER2-low expression in breast cancers based on hematoxylin–eosin-stained slides
10.1186/s13058-025-01998-8 · 2025 · External reference
Automated quantification of Ki-67 expression in breast cancer from H&E-stained slides using a transformer-based regression model
10.1186/s13058-025-02149-9 · 2025 · External reference
Contrastive learning-based histopathological features infer molecular subtypes and clinical outcomes of breast cancer from unannotated whole slide images
10.1016/j.compbiomed.2024.107997 · 2024 · External reference
Validation of an artificial intelligence model for breast cancer molecular subtyping using hematoxylin and eosin-stained whole-slide images in a population-based cohort
10.3390/cancers17193234 · 2025 · External reference
Multi-attribute embedding network for breast cancer subtyping prediction reveals intrinsic molecular properties hidden in H&E images
10.1016/j.bspc.2025.109189 · 2026 · External reference
Synergistic H&E and IHC image analysis by AI predicts cancer biomarkers and survival outcomes in colorectal and breast cancer
10.1038/s43856-025-01045-9 · 2025 · External reference
Cross-modality learning for predicting immunohistochemistry biomarkers from hematoxylin and eosin–stained whole slide images
10.1016/j.ajpath.2025.08.014 · 2025 · External reference
From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology
10.1038/s41596-024-01047-2 · 2025 · External reference
