Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …

Breast cancer is one of the most common and deadliest cancers among women. Since
histopathological images contain sufficient phenotypic information, they play an …

Breast cancer (BC) classification has become a point of concern within the field of
biomedical informatics in the health care sector in recent years. This is because it is the …

Computer-aided image analysis for better understanding of images has been time-honored
approaches in the medical computing field. In the conventional machine learning approach …

The proportion of COVID-19 patients is significantly expanding around the world. Treatment
with serious consideration has become a significant problem. Identifying clinical indicators of …

Simple Summary This study develops an arithmetic optimization algorithm with deep-
learning-based histopathological breast cancer classification (AOADL-HBCC) technique for …

Accurate classification of medical images is of great importance for correct disease
diagnosis. The automation of medical image classification is of great necessity because it …

Deep learning techniques, which use a massive technology known as convolutional neural
networks, have shown excellent results in a variety of areas, including image processing …

Deep learning-based approaches have become widespread in medical fields and have
achieved profound success in recent years. Nonetheless, most of these approaches cannot …

The most effective and feasible method for treating cancer is early diagnosis of breast
cancer. An appropriate software tool, known as computer-aided diagnosis, helps doctors …