ArticleJournal of imaging2020
Detection of HER2 from Haematoxylin-Eosin Slides Through a Cascade of Deep Learning Classifiers via Multi-Instance Learning.
Article in Journal of imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Integrating Artificial Intelligence into Breast Cancer Histopathology: Toward Improved Diagnosis and Prognosis.Cancers · 2026Review
- Challenges & recommendations for identification of human epidermal growth factor receptor -2 (HER2)-low metastatic breast cancer in India: Expert opinion statement.The Indian journal of medical research · 2025Review
- Characterisation of HER2-Driven Morphometric Signature in Breast Cancer and Prediction of Risk of Recurrence.Cancer medicine · 2025Article
- AI in Histopathology Explorer for comprehensive analysis of the evolving AI landscape in histopathology.NPJ digital medicine · 2025Article
- Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review.Journal of pathology informatics · 2024Article
- Deep learning application in prediction of cancer molecular alterations based on pathological images: a bibliographic analysis via CiteSpace.Journal of cancer research and clinical oncology · 2024Article
- Weakly-supervised deep learning models enable HER2-low prediction from H &E stained slides.Breast cancer research : BCR · 2024Article
- Prognostic impact of HER2 biomarker levels in trastuzumab-treated early HER2-positive breast cancer.Breast cancer research : BCR · 2024Article
- MGGAN: A multi-generator generative adversarial network for breast cancer immunohistochemical image generation.Heliyon · 2023Article
- Low and Ultra-Low HER2 in Human Breast Cancer: An Effort to Define New Neoplastic Subtypes.International journal of molecular sciences · 2023Review
- Review
- Biological insights and novel biomarker discovery through deep learning approaches in breast cancer histopathology.NPJ breast cancer · 2023Review
- Deep Learning-Based Prediction of Molecular Tumor Biomarkers from H&E: A Practical Review.Journal of personalized medicine · 2022Review
- HEROHE Challenge: Predicting HER2 Status in Breast Cancer from Hematoxylin-Eosin Whole-Slide Imaging.Journal of imaging · 2022Article
- HER2 Low, Ultra-low, and Novel Complementary Biomarkers: Expanding the Spectrum of HER2 Positivity in Breast Cancer.Frontiers in molecular biosciences · 2022Review
- Deep Learning in Medical Image Analysis.Journal of imaging · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is the most frequently diagnosed cancer in woman. The correct identification of the HER2 receptor is a matter of major importance when dealing with breast cancer: an over-expression of HER2 is associated with aggressive clinical behaviour; moreover, HER2 targeted therapy results in a significant improvement in the overall survival rate. In this work, we employ a pipeline based on a cascade of deep neural network classifiers and multi-instance learning to detect the presence of HER2 from Haematoxylin-Eosin slides, which partly mimics the pathologist's behaviour by first recognizing cancer and then evaluating HER2. Our results show that the proposed system presents a good overall effectiveness. Furthermore, the system design is prone to further improvements that can be easily deployed in order to increase the effectiveness score.
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