Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review

EH Houssein, MM Emam, AA Ali… - Expert Systems with …, 2021 - Elsevier
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 …

[HTML][HTML] A review of machine learning techniques for the classification and detection of breast cancer from medical images

R Jalloul, HK Chethan, R Alkhatib - Diagnostics, 2023 - mdpi.com
Cancer is an incurable disease based on unregulated cell division. Breast cancer is the
most prevalent cancer in women worldwide, and early detection can lower death rates …

Breast cancer classification from histopathological images using patch-based deep learning modeling

I Hirra, M Ahmad, A Hussain, MU Ashraf… - IEEE …, 2021 - ieeexplore.ieee.org
Accurate detection and classification of breast cancer is a critical task in medical imaging
due to the complexity of breast tissues. Due to automatic feature extraction ability, deep …

Deep learning model for fully automated breast cancer detection system from thermograms

EA Mohamed, EA Rashed, T Gaber, O Karam - PloS one, 2022 - journals.plos.org
Breast cancer is one of the most common diseases among women worldwide. It is
considered one of the leading causes of death among women. Therefore, early detection is …

Breast cancer segmentation from thermal images based on chaotic salp swarm algorithm

A Ibrahim, S Mohammed, HA Ali, SE Hussein - IEEE Access, 2020 - ieeexplore.ieee.org
Breast cancer is one of the most common types of cancer and early detection can
significantly decrease the associated mortality rate. Different kinds of segmentation methods …

[PDF][PDF] Meta-heuristics for feature selection and classification in diagnostic breast cancer

DS Khafaga, AA Alhussan… - … , Materials & Continua, 2022 - researchgate.net
One of the most common kinds of cancer is breast cancer. The early detection of it may help
lower its overall rates of mortality. In this paper, we robustly propose a novel approach for …

Deep federated machine learning-based optimization methods for liver tumor diagnosis: A review

AM Anter, L Abualigah - Archives of Computational Methods in …, 2023 - Springer
Computer-aided liver diagnosis helps doctors accurately identify liver abnormalities and
reduce the risk of liver surgery. Early diagnosis and detection of liver lesions depend mainly …

Breast cancer identification via thermography image segmentation with a gradient vector flow and a convolutional neural network

S Tello-Mijares, F Woo, F Flores - Journal of healthcare …, 2019 - Wiley Online Library
Breast cancer is the most common cancer among women worldwide with about half a million
cases reported each year. Mammary thermography can offer early diagnosis at low cost if …

A hybrid SA-MFO algorithm for function optimization and engineering design problems

GI Sayed, AE Hassanien - Complex & Intelligent Systems, 2018 - Springer
This paper presents a hybrid algorithm based on using moth-flame optimization (MFO)
algorithm with simulated annealing (SA), namely (SA-MFO). The proposed SA-MFO …

Convolutional neural networks for static and dynamic breast infrared imaging classification

MFO Baffa, LG Lattari - 2018 31st SIBGRAPI Conference on …, 2018 - ieeexplore.ieee.org
Breast cancer is the most frequent type of cancer among women. Since early diagnosis
provides a better prognosis, different techniques have been developed by researchers all …