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)...
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...
Biological age is an important indicator of organ functions and health. Although mammograms are widely used in breast cancer screening, the potential of mammogram-based biological age predictors remains underexplored. Here, we propose a deep learning...
PURPOSE: To evaluate and compare patient perceptions of artificial intelligence (AI) use in mammogram interpretation across academic and safety-net healthcare settings.
BACKGROUND: Hormone receptor (HR) status guides breast cancer therapy. Deep learning (DL) applied to contrast-enhanced mammography (CEM) might offer a noninvasive means for HR status prediction, but class imbalance challenges model development and as...
The classification of malignant versus benign microcalcifications in mammograms remains a critical yet challenging task in breast cancer screening. Deep learning models, particularly convolutional neural networks, have demonstrated promising results;...
Breast cancer is a significant public health concern, and early detection is critical for triaging high-risk patients. Sequential screening mammograms can provide important spatiotemporal information about changes in breast tissue over time, which ma...
Breast cancer detection and diagnosis remain challenging due to the complexity of tumor tissues and image quality variations, which hinder early and accurate identification. Timely diagnosis is vital for initiating treatment and improving patient out...
This study focuses on improving the detection of breast cancer at an early stage. The common approach for diagnosing breast cancer is mammography, but it is quite tedious as it is subject to subjective analysis. To address these challenges, the resea...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.