ArticleDiagnostics (Basel, Switzerland)2023
Immunohistochemical HER2 Recognition and Analysis of Breast Cancer Based on Deep Learning.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Computational methods, clinical evidence, and translational readiness for artificial intelligence for HER2 assessment using silver in situ hybridization (SISH).Breast cancer research : BCR · 2026Pooled it
- HScore as a diagnostic tool in ERBB2 equivocal (immunohistochemistry 2+) breast cancer.Laboratory medicine · 2026Article
- Automatic grading of HER2 immunohistochemical whole-slide images based on a multi-scale hierarchical graph neural network.Frontiers in public health · 2026Article
- HER2-IHC-40x: A high-resolution histopathology dataset for HER2 IHC scoring in breast cancer.Data in brief · 2025Article
- Transformer-BasedDiagnostics (Basel, Switzerland) · 2025Article
- Toward Optimizing the Impact of Digital Pathology and Augmented Intelligence on Issues of Diagnosis, Grading, Staging, and Classification.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025Review
- Automated Detection of Kaposi Sarcoma-Associated Herpesvirus-Infected Cells in Immunohistochemical Images of Skin Biopsies.JCO global oncology · 2025Article
- Next-generation sequencing based deep learning model for prediction of HER2 status and response to HER2-targeted neoadjuvant chemotherapy.Journal of cancer research and clinical oncology · 2025Article
- HER2 immunohistochemical expression and its association with clinicopathological features of gastric adenocarcinoma in Uganda.Turkish journal of surgery · 2024Article
- Predicting HER2 Status Associated with Breast Cancer Aggressiveness Using Four Machine Learning Models.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Deep learning applications in breast cancer histopathological imaging: diagnosis, treatment, and prognosis.Breast cancer research : BCR · 2024Review
- The Performance and Clinical Applicability of HER2 Digital Image Analysis in Breast Cancer: A Systematic Review.Cancers · 2024Review
- Prediction of HER2 Status Based on Deep Learning in H&E-Stained Histopathology Images of Bladder Cancer.Biomedicines · 2024Article
Corrections and comments
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6 authors.
Funding
Abstract
Breast cancer is one of the common malignant tumors in women. It seriously endangers women's life and health. The human epidermal growth factor receptor 2 (HER2) protein is responsible for the division and growth of healthy breast cells. The overexpression of the HER2 protein is generally evaluated by immunohistochemistry (IHC). The IHC evaluation criteria mainly includes three indexes: staining intensity, circumferential membrane staining pattern, and proportion of positive cells. Manually scoring HER2 IHC images is an error-prone, variable, and time-consuming work. To solve these problems, this study proposes an automated predictive method for scoring whole-slide images (WSI) of HER2 slides based on a deep learning network. A total of 95 HER2 pathological slides from September 2021 to December 2021 were included. The average patch level precision and f1 score were 95.77% and 83.09%, respectively. The overall accuracy of automated scoring for slide-level classification was 97.9%. The proposed method showed excellent specificity for all IHC 0 and 3+ slides and most 1+ and 2+ slides. The evaluation effect of the integrated method is better than the effect of using the staining result only.
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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.