The intrinsic complexity of biological processes often hides the role of dynamic microenvironmental cues in the development of pathological states. Microphysiological systems (MPSs) are emerging technological platforms that model dynamics of tissue-...
This study integrates ultrasound Radiomics with clinical data to enhance the diagnostic accuracy of HER-2 expression status in breast cancer, aiming to provide more reliable treatment strategies for this aggressive disease. We included ultrasound ima...
Breast cancer is characterized by the proliferation of abnormal breast cells that eventually turn into malignant tumors. These cancer cells can metastasize to be life-threatening and fatal. An intricate mix of environmental factors and individual gen...
. Temporal changes in volumetric breast density (VBD) may serve as prognostic biomarkers for predicting the risk of future breast cancer development. However, accurately measuring VBD from archived x-ray mammograms remains challenging. In a previous ...
Heterogeneity of breast cancer poses several challenges for detection and treatment. With next-generation sequencing, we can now map the transcriptional profile of each patient's breast tissue, which has the potential for identifying and characterizi...
Ecotoxicology and environmental safety
Jul 22, 2025
BACKGROUND: Breast cancer (BRCA) is the most common malignancy in women worldwide. Selenium (Se), a crucial trace element, significantly impacts BRCA patient survival, although its roles in tumorigenesis, the tumor immune microenvironment (TIME), and...
Journal of experimental & clinical cancer research : CR
Jul 21, 2025
Breast cancer (BC) remains a leading cause of cancer-related mortality in women, with complex mechanisms driving its initiation, progression, and resistance to therapy. In recent years, the tumor microenvironment (TME) has gained attention for its cr...
INTRODUCTION: Accurate breast cancer risk prediction is essential for early detection and personalized prevention strategies. While traditional models, such as Gail and Tyrer-Cuzick, are widely utilized, machine learning-based approaches may offer en...
As digital imaging technology advances, accurate classification of 2D breast cancer images becomes increasingly crucial for early detection and staging. This paper introduces a novel classification approach that integrates deep learning, sparse codin...
Advancements in diagnostic technology are required to improve patient outcomes and facilitate early diagnosis, as breast cancer is a substantial global health concern. This research discusses the creation of a unique Deep Learning (DL) Ensemble Deep ...
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