Breast cancer is the most common cancer among women worldwide. Early-stage diagnosis
of this disease can significantly improve the efficiency of treatment. Computer-Aided …

For breast cancer diagnosis, computer-aided classification of histopathological images is of
critical importance for correct and early diagnosis. Transfer learning approaches for feature …

In computer vision, particularly in label categorization, attributing features such as color,
shape, and tissue size to each category presents a formidable challenge. Dense features …

Breast cancer is one of the leading death cause among women nowadays. Several methods
have been proposed for the detection of breast cancer. Various machine learning-based …

Breast cancer is one of the most common invading cancers in women. Analyzing breast
cancer is nontrivial and may lead to disagreements among experts. Although deep learning …

There are several breast cancer datasets for building Computer Aided Diagnosis systems
(CADs) using either deep learning or traditional models. However, most of these datasets …

A crucial element in the diagnosis of breast cancer is the utilization of a classification method
that is efficient, lightweight, and precise. Convolutional neural networks (CNNs) have …

Computer‐aided classification of pathological images is of the great significance for breast
cancer diagnosis. In recent years, deep learning methods for breast cancer pathological …

Deep learning, as one of the currently most popular computer science research trends,
improves neural networks, which has more and deeper layers allowing higher abstraction …

Breast tumor detection and classification on the Internet of Medical Things (IoMT) can be
automated with the potential of Artificial Intelligence (AI). Deep learning models rely on large …