Breast cancer is a common type of cancer in women, denoted by the uncontrolled growth of
cells in breast tissue. Thus, manually detecting breast cancer is time-consuming and …

Recently, transfer learning approaches appeared to reduce the need for many classified
medical images. However, these approaches still contain some limitations due to the …

Breast cancer is a significant health concern among women. Prompt diagnosis can diminish
the mortality rate and direct patients to take steps for cancer treatment. Recently, deep …

Breast cancer is one of the most common causes of cancer-related death in women
worldwide. Early and accurate diagnosis of breast cancer may significantly increase the …

The Real-time automated medical image diagnosis system could assist pathologist for
speed-up diagnosis process for confirming the findings. In this paper, various issues …

Medical image analysis methods for mammograms, ultrasound, and magnetic resonance
imaging (MRI) cannot provide the underline features on the cellular level to understand the …

Breast cancer is a lethal illness that has a high mortality rate. In treatment, the accuracy of
diagnosis is crucial. Machine learning and deep learning may be beneficial to doctors. The …

Early detection of breast cancer is an essential procedure to reduce the mortality rate among
women. In this paper, a new AI-based computer-aided diagnosis (CAD) framework called …

Breast cancer is one of the most common types of cancer among women, which requires
building smart systems to help doctors and early detection of cancer. Deep learning …

In this study, we proposed a novel convolutional neural network (CNN) architecture for
classification of benign and malignant breast cancer (BC) in histological images. To improve …