Breast cancer detection using deep learning: Datasets, methods, and challenges ahead

RA Dar, M Rasool, A Assad - Computers in biology and medicine, 2022 - Elsevier
Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …

Deep learning with radiomics for disease diagnosis and treatment: challenges and potential

X Zhang, Y Zhang, G Zhang, X Qiu, W Tan, X Yin… - Frontiers in …, 2022 - frontiersin.org
The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …

The state of the art of deep learning models in medical science and their challenges

C Bhatt, I Kumar, V Vijayakumar, KU Singh… - Multimedia Systems, 2021 - Springer
With time, AI technologies have matured well and resonated in various domains of applied
sciences and engineering. The sub-domains of AI, machine learning (ML), deep learning …

Convolutional neural networks for breast cancer detection in mammography: A survey

L Abdelrahman, M Al Ghamdi, F Collado-Mesa… - Computers in biology …, 2021 - Elsevier
Despite its proven record as a breast cancer screening tool, mammography remains labor-
intensive and has recognized limitations, including low sensitivity in women with dense …

Artificial intelligence for breast cancer analysis: Trends & directions

SM Shah, RA Khan, S Arif, U Sajid - Computers in Biology and Medicine, 2022 - Elsevier
Breast cancer is one of the leading causes of death among women. Early detection of breast
cancer can significantly improve the lives of millions of women across the globe. Given …

Systematic review of computing approaches for breast cancer detection based computer aided diagnosis using mammogram images

DA Zebari, DA Ibrahim, DQ Zeebaree… - Applied Artificial …, 2021 - Taylor & Francis
Breast cancer is one of the most prevalent types of cancer that plagues females. Mortality
from breast cancer could be reduced by diagnosing and identifying it at an early stage. To …

A brief survey on breast cancer diagnostic with deep learning schemes using multi-image modalities

T Mahmood, J Li, Y Pei, F Akhtar, A Imran… - IEEe …, 2020 - ieeexplore.ieee.org
Patients with breast cancer are prone to serious health-related complications with higher
mortality. The primary reason might be a misinterpretation of radiologists in recognizing …

A comprehensive survey on deep-learning-based breast cancer diagnosis

MF Mridha, MA Hamid, MM Monowar, AJ Keya, AQ Ohi… - Cancers, 2021 - mdpi.com
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 …

Multi-modal retinal image classification with modality-specific attention network

X He, Y Deng, L Fang, Q Peng - IEEE transactions on medical …, 2021 - ieeexplore.ieee.org
Recently, automatic diagnostic approaches have been widely used to classify ocular
diseases. Most of these approaches are based on a single imaging modality (eg, fundus …

Deep learning cascaded feature selection framework for breast cancer classification: Hybrid CNN with univariate-based approach

NA Samee, G Atteia, S Meshoul, MA Al-antari… - Mathematics, 2022 - mdpi.com
With the help of machine learning, many of the problems that have plagued mammography
in the past have been solved. Effective prediction models need many normal and tumor …