A systematic literature review of breast cancer diagnosis using machine intelligence techniques
Breast cancer is one of the most common diseases in women; it can have long-term
implications and can even be fatal. However, early detection, achieved through recent …
implications and can even be fatal. However, early detection, achieved through recent …
[HTML][HTML] A survey of convolutional neural network in breast cancer
Aims A large number of clinical trials have proved that if breast cancer is diagnosed at an
early stage, it could give patients more treatment options and improve the treatment effect …
early stage, it could give patients more treatment options and improve the treatment effect …
Multi-class classification of breast cancer using 6b-net with deep feature fusion and selection method
Breast cancer has now overtaken lung cancer as the world's most commonly diagnosed
cancer, with thousands of new cases per year. Early detection and classification of breast …
cancer, with thousands of new cases per year. Early detection and classification of breast …
SELF: a stacked-based ensemble learning framework for breast cancer classification
Nowadays, breast cancer is the most prevalent and jeopardous disease in women after lung
cancer. During the past few decades, a substantial amount of cancer cases have been …
cancer. During the past few decades, a substantial amount of cancer cases have been …
Histopathological breast cancer classification using CNN
EO Simonyan, JA Badejo, JS Weijin - Materials Today: Proceedings, 2024 - Elsevier
In the year 2021, there were 2.26 million new diagnoses of breast cancer cases among
women globally. Over the years, various imaging methods such as mammography, Magnetic …
women globally. Over the years, various imaging methods such as mammography, Magnetic …
State-of-the-art of breast cancer diagnosis in medical images via convolutional neural networks (cnns)
Early detection of breast cancer is crucial for a better prognosis. Various studies have been
conducted where tumor lesions are detected and localized on images. This is a narrative …
conducted where tumor lesions are detected and localized on images. This is a narrative …
Vit-deit: An ensemble model for breast cancer histopathological images classification
A Alotaibi, T Alafif, F Alkhilaiwi, Y Alatawi… - … Innovations in Smart …, 2023 - ieeexplore.ieee.org
Breast cancer is the most common cancer in the world and the second most common type of
cancer that causes death in women. The timely and accurate diagnosis of breast cancer …
cancer that causes death in women. The timely and accurate diagnosis of breast cancer …
TransNet: a comparative study on breast carcinoma diagnosis with classical machine learning and transfer learning paradigm
Breast Carcinoma is a deadly disease; therefore, timely diagnosis is one of the most critical
concerns that must be addressed globally since it can significantly enhance overall survival …
concerns that must be addressed globally since it can significantly enhance overall survival …
Rapid tri-net: breast cancer classification from histology images using rapid tri-attention network
PB Salunkhe, PS Patil - Multimedia Tools and Applications, 2024 - Springer
Nowadays, people all over the world are facing several problems related to the deadly
disease of breast cancer. The research on breast cancer detection using existing techniques …
disease of breast cancer. The research on breast cancer detection using existing techniques …
Selecting the optimal transfer learning model for precise breast cancer diagnosis utilizing pre-trained deep learning models and histopathology images
Abstract Background Every year, around 1.5 million women worldwide receive a breast
cancer diagnosis, which is why the mortality rate for women is rising. Scientists have …
cancer diagnosis, which is why the mortality rate for women is rising. Scientists have …