Medical images are helpful for the diagnosis, treatment, and evaluation of diseases. Precise
medical image segmentation improves diagnosis and decision-making, aiding intelligent …

Simple Summary A radial basis function neural network (RBFNN) is proposed for identifying
and diagnosing non-linear systems. The neural network developed was optimized not only …

Numerous educational institutions utilize data mining techniques to manage student
records, particularly those related to academic achievements, which are essential in …

Purpose To construct a nomogram based on sonogram features and radiomics features to
differentiate granulomatous lobular mastitis (GLM) from invasive breast cancer (IBC) …

Breast cancer (BC) is the most prominent form of cancer among females all over the world.
The current methods of BC detection include X-ray mammography, ultrasound, computed …

For over a decade, large cancer-related datasets (big data) have continuously been
produced and made publicly available to the scientific community. A current challenge is …

Simple Summary The appearance of microcalcifications in mammogram images is an
essential predictor for radiologists to detect early-stage breast cancer. This study aims to …

Introduction Breast cancer is a significant public health concern in Jordan. It is the most
common cancer among Jordanian women. Despite its high incidence and advanced stage …

Breast cancer is a major health threat, with early detection crucial for improving cure and
survival rates. Current systems rely on imaging technology, but digital pathology and …

With the versatility and exponential growth of IoT solutions, the probability of being attacked
has increased. Resource constraint IoT devices raised a challenge for the security handler …