Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …

Breast cancer is the second leading cause of death for women, so accurate early detection
can help decrease breast cancer mortality rates. Computer-aided detection allows …

Simple Summary Breast cancer is the most common cancer, which resulted in the death of
700,000 people around the world in 2020. Various imaging modalities have been utilized to …

Convolutional Neural Network (CNN) models are a type of deep learning architecture
introduced to achieve the correct classification of breast cancer. This paper has a two-fold …

Simple Summary Breast cancer was diagnosed in 2.3 million women, and around 685,000
deaths from breast cancer were recorded globally in 2020, making it the most common …

Breast cancer is one of the worst illnesses, with a higher fatality rate among women globally.
Breast cancer detection needs accurate mammography interpretation and analysis, which is …

Background Breast cancer is a major public health concern, and early diagnosis and
classification are critical for effective treatment. Machine learning and deep learning …

The incidence and mortality rate of Breast Cancer (BC) are global problems for women, with
over 2.1 million new diagnoses each year worldwide. There is no age range, race, or …

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 …

This paper provides a critical review of the literature on deep learning applications in breast
tumor diagnosis using ultrasound and mammography images. It also summarizes recent …