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Receptor, ErbB-2

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Non-invasive Assessment of Human Epidermal Growth Factor Receptor 2 Expression in Gastric Cancer Based on Deep Learning: A Computed Tomography-based Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: The expression of human epidermal growth factor receptor 2 (HER2) in gastric cancer is closely associated with its treatment outcomes and prognosis. This study aims to develop and validate a HER2 prediction model based on co...

Multimodal integration using a machine learning approach facilitates risk stratification in HR+/HER2- breast cancer.

Cell reports. Medicine
Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common type of breast cancer, with continuous recurrence remaining an important clinical issue. Current relapse predictive models in H...

Classifying the molecular subtype of breast cancer using vision transformer and convolutional neural network features.

Breast cancer research and treatment
PURPOSE: Identification of the molecular subtypes in breast cancer allows to optimize treatment strategies, but usually requires invasive needle biopsy. Recently, non-invasive imaging has emerged as promising means to classify them. Magnetic resonanc...

Artificial Intelligence for Predicting HER2 Status of Gastric Cancer Based on Whole-Slide Histopathology Images: A Retrospective Multicenter Study.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Human epidermal growth factor receptor 2 (HER2) positive gastric cancer (GC) shows a robust response to the combined therapy based HER2-targeted therapy. The application of these therapies is highly dependent on the evaluation of tumor HER2 status. H...

From text to insight: A natural language processing-based analysis of burst and research trends in HER2-low breast cancer patients.

Ageing research reviews
With the intensification of population aging, the proportion of elderly breast cancer patients is continuously increasing, among which those with low HER2 expression account for approximately 45 %-55 % of all cases within traditional HER2-negative br...

Discovery of New HER2 Inhibitors via Computational Docking, Pharmacophore Modeling, and Machine Learning.

Molecular informatics
The human epidermal growth factor receptor 2 (HER2) is a critical oncogene implicated in the development of various aggressive cancers, particularly breast cancer. Discovering novel HER2 inhibitors is crucial for expanding therapeutic options for HER...

An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.

Scientific reports
Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strateg...

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
INTRODUCTION: For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 (HER2) is closely related to their prognosis and treatment decisions. This study aimed to further improve the accuracy and efficiency of HER2 amplific...

Weakly supervised multi-modal contrastive learning framework for predicting the HER2 scores in breast cancer.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Human epidermal growth factor receptor 2 (HER2) is an important biomarker for prognosis and prediction of treatment response in breast cancer (BC). HER2 scoring is typically evaluated by pathologist microscopic observation on immunohistochemistry (IH...