PURPOSE: This study aimed to develop a Deep Learning Radiomics integrated model (DLRN), which combines photoacoustic/ultrasound(PA/US)imaging with clinical and radiomics features to distinguish between luminal and non-luminal BC in a preoperative set...
Oestrogen receptor alpha (ERα)-positive (ER+) breast cancers are driven by the binding of 17β-oestradiol (E2) to ERα, which transcriptionally regulates target genes. Although microarrays and conventional RNA sequencing have identified E2 target genes...
BACKGROUND: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, rad...
Medical science monitor : international medical journal of experimental and clinical research
Sep 9, 2025
BACKGROUND This study used CT imaging analyzed with deep learning techniques to assess the diagnostic accuracy of lung metastasis detection in patients with breast cancer. The aim of the research was to create and verify a system for detecting malign...
PURPOSE: To develop and validate a deep learning-based model for automated evaluation of mammography phantom images, with the goal of improving inter-radiologist agreement and enhancing the efficiency of quality control within South Korea's national ...
PURPOSE: To investigate the effectiveness of an integrated deep-learning (DL) algorithm, the Mixture of Radiological Findings Specific Experts (MoRFSE), in breast cancer classification by imitating the diagnostic decision-making process of radiologis...
Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on...
Extracellular vesicles (EVs) have emerged as promising biomarkers in cancer diagnostics. However, rapid and nondestructive isolation of EVs from plasma remains challenging due to the presence of abundant interferents with smaller sizes (e.g., protein...
The most prevalent cancer in women worldwide, breast cancer, greatly benefits from early identification for better prognoses. But traditional diagnostic techniques, like biopsies and mammograms, can require invasive procedures and lack accuracy. The ...
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 29, 2025
BACKGROUND: This study aimed to develop a predictive model integrating multi-sequence MRI radiomics, deep learning features, and habitat imaging to forecast pathological complete response (pCR) in breast cancer patients undergoing neoadjuvant therapy...
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