A systematic literature review of breast cancer diagnosis using machine intelligence techniques

V Nemade, S Pathak, AK Dubey - Archives of Computational Methods in …, 2022 - Springer
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 …

Deep convolutional neural networks for computer-aided breast cancer diagnostic: a survey

P Oza, P Sharma, S Patel, P Kumar - Neural computing and applications, 2022 - Springer
Advances in deep learning networks, especially deep convolutional neural networks
(DCNNs), are causing remarkable breakthroughs in radiology and imaging sciences. These …

[HTML][HTML] Deep learning in mammography images segmentation and classification: Automated CNN approach

WM Salama, MH Aly - Alexandria Engineering Journal, 2021 - Elsevier
In this work, a new framework for breast cancer image segmentation and classification is
proposed. Different models including InceptionV3, DenseNet121, ResNet50, VGG16 and …

Predictive modeling for breast cancer classification in the context of Bangladeshi patients by use of machine learning approach with explainable AI

T Islam, MA Sheakh, MS Tahosin, MH Hena… - Scientific Reports, 2024 - nature.com
Breast cancer has rapidly increased in prevalence in recent years, making it one of the
leading causes of mortality worldwide. Among all cancers, it is by far the most common …

[HTML][HTML] Breast cancer mammograms classification using deep neural network and entropy-controlled whale optimization algorithm

S Zahoor, U Shoaib, IU Lali - Diagnostics, 2022 - mdpi.com
Breast cancer has affected many women worldwide. To perform detection and classification
of breast cancer many computer-aided diagnosis (CAD) systems have been established …

Inconsistent performance of deep learning models on mammogram classification

X Wang, G Liang, Y Zhang, H Blanton… - Journal of the American …, 2020 - Elsevier
Objectives Performance of recently developed deep learning models for image classification
surpasses that of radiologists. However, there are questions about model performance …

Artificial neural network based breast cancer screening: a comprehensive review

S Bharati, P Podder, M Mondal - arxiv preprint arxiv:2006.01767, 2020 - arxiv.org
Breast cancer is a common fatal disease for women. Early diagnosis and detection is
necessary in order to improve the prognosis of breast cancer affected people. For predicting …

Integrating segmentation information into CNN for breast cancer diagnosis of mammographic masses

L Tsochatzidis, P Koutla, L Costaridou… - Computer Methods and …, 2021 - Elsevier
Abstract Background and Objectives Segmentation of mammographic lesions has been
proven to be a valuable source of information, as it can assist in both extracting shape …

Breast cancer detection: Shallow convolutional neural network against deep convolutional neural networks based approach

HS Das, A Das, A Neog, S Mallik, K Bora… - Frontiers in …, 2023 - frontiersin.org
Introduction: Of all the cancers that afflict women, breast cancer (BC) has the second-highest
mortality rate, and it is also believed to be the primary cause of the high death rate. Breast …

A deep learning model using data augmentation for detection of architectural distortion in whole and patches of images

ON Oyelade, AE Ezugwu - Biomedical Signal Processing and Control, 2021 - Elsevier
Breast cancer is now widely known to be the second most lethal disease among women.
Computer-aided detection (CAD) systems, deep learning (DL) in particular, have continued …