ArticleOncology letters2023
HER2 classification in breast cancer cells: A new explainable machine learning application for immunohistochemistry.
Article in Oncology letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
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Who cites it
11 citing papers in PubMed, 26 citations in OpenAlex.
- Digital image analysis improves diagnostic accuracy of HER2-low and HER2-ultralow breast cancer: a step towards personalised medicine.Virchows Archiv : an international journal of pathology · 2026Article
- First-time detection of treatable congenital heart disease - a study of school-aged children in the community of three regions in China.BMC public health · 2026Article
- Classification of human epidermal growth factor receptor 2 expression in cancerous breast tissue through artificial intelligenceBiomedica : revista del Instituto Nacional de Salud · 2025Article
- Mortality Prediction Modeling for Patients with Breast Cancer Based on Explainable Machine Learning.Cancers · 2024Article
- Construction and interpretation of machine learning-based prognostic models for survival prediction among intestinal-type and diffuse-type gastric cancer patients.World journal of surgical oncology · 2024Article
- Predicting HER2 Status Associated with Breast Cancer Aggressiveness Using Four Machine Learning Models.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review.Cancer innovation · 2024Article
- The Performance and Clinical Applicability of HER2 Digital Image Analysis in Breast Cancer: A Systematic Review.Cancers · 2024Review
- A Systematic Review of Real-Time Deep Learning Methods for Image-Based Cancer Diagnostics.Journal of multidisciplinary healthcare · 2024Article
- Application of SHAP for Explainable Machine Learning on Age-Based Subgrouping Mammography Questionnaire Data for Positive Mammography Prediction and Risk Factor Identification.Healthcare (Basel, Switzerland) · 2023Article
- Adaptive Aquila Optimizer with Explainable Artificial Intelligence-Enabled Cancer Diagnosis on Medical Imaging.Cancers · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The immunohistochemical (IHC) evaluation of epidermal growth factor 2 (HER2) for the diagnosis of breast cancer is still qualitative with a high degree of inter-observer variability, and thus requires the incorporation of complementary techniques such as fluorescent
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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.