BACKGROUND: Data on neoadjuvant treatment with trastuzumab biosimilars, particularly CT-P6, in combination with pertuzumab, are limited. This study evaluates the efficacy, tolerability, and immunogenicity of CT-P6 plus pertuzumab and chemotherapy, in...
AIMS: HER2/neu gene is amplified in 15%-20% of invasive breast cancers (IBCs), serving as critical prognostic and predictive marker. HER2-targeted therapies have improved outcomes for HER2-positive patients, highlighting the importance of accurate as...
Amino acid metabolism plays a critical role in tumor growth and immune regulation, yet its comprehensive function in breast cancer remains underexplored. We developed an amino acid metabolism-related gene signature (AAMRGS) to predict prognosis and t...
Biomedical physics & engineering express
Jan 6, 2026
. To classify digital mammograms based on radiological findings using morphology and texture descriptors with artificial neural networks (ANN) for breast cancer detection.The mammography dataset from High Specialty Regional Hospital of Oaxaca (HRAEO)...
British journal of hospital medicine (London, England : 2005)
Dec 19, 2025
Artificial intelligence (AI) holds significant promise in the fields of diagnostics and therapeutics, particularly in cancer management. AI has been extensively applied in various aspects of breast cancer care. Numerous studies and reviews have been ...
OBJECTIVE: To explore the biological foundations of MRI-based prognostic imaging signatures (including radiomics and deep learning signatures) in breast cancer, and to assess the methodological quality of existing studies.
Recent studies have established the gut microbiome as a crucial player in breast cancer diagnosis, progression, and treatment. Distinct microbial patterns have shown promise as non-invasive diagnostic and prognostic biomarkers, supporting patient str...
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Dec 16, 2025
PURPOSE: This study aimed to establish and validate a machine learning model for predicting moderate-to-severe cancer-related fatigue (CRF) 2 years after completion of anti-tumor therapy in breast cancer patients.
Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsiny
Dec 15, 2025
The article considers issues of training models of convolutional neuronic network (CNN) for automated identification of point functions of visualization to discern mammography pictures belonging to negative, false benign and malignant cases, targetin...
While Fine needle aspiration cytology (FNAC) and mammography are both used to diagnose breast lesions, FNAC is generally more accurate than mammograms for predicting breast cancer. It is also gaining popularity as an early detection tool due to its r...
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