Around the world, brain tumors are becoming the leading cause of mortality. The inability to
undertake a timely tumor diagnosis is the primary cause of this pandemic. Brain cancer …

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

Adaptive self-learning is a promising technique in medical image analysis that enables deep
learning models to adapt to changes in image distribution over time. As medical image data …

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 …

Breast cancer, with its high mortality, faces diagnostic challenges due to variability in
mammography quality and breast densities, leading to inconsistencies in radiological …

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

Artificial Intelligence (AI) is increasingly sha** the field of dermatology, particularly in the
detection and management of skin cancers, including melanoma, basal cell carcinoma …

This paper proposes an approach to enhance the differentiation task between benign and
malignant Breast Tumors (BT) using histopathology images from the BreakHis dataset. The …

Breast cancer (BC) is a global problem, largely due to a shortage of knowledge and early
detection. The speed-up process of detection and classification is crucial for effective cancer …

Capsid protein is a pathogenic protein that needs to be examined because it helps in the
virus's proliferation and mutation. Due to this protein, the virus can replicate and reproduce …