A composite hybrid feature selection learning-based optimization of genetic algorithm for breast cancer detection

AA Farid, G Selim, H Khater - 2020 - preprints.org
Breast cancer is a significant health issue across the world. Breast cancer is the most widely-
diagnosed cancer in women; early-stage diagnosis of disease and therapies increase …

MLP-TLBO: Combining Multi-Layer Perceptron Neural Network and Teaching-Learning-Based Optimization for Breast Cancer Detection

Y Cui, X Li, Y Wang, W Yuan, X Cheng… - Cybernetics and …, 2022 - Taylor & Francis
Symptoms and types of breast cancer, like most other diseases, vary from person to person.
This is while some infected people may not have any symptoms. Breast cancer is one of the …

Prediction of breast cancer based on computer vision and artificial intelligence techniques

AI Khan, YB Abushark, F Alsolami, A Almalawi… - Measurement, 2023 - Elsevier
Breast cancer is a leading cause of mortality among women. Early detection will increase
the chances of successful treatment and minimize the death rate. Even though many studies …

Insight into breast cancer detection: new hybrid feature selection method

WM Shaban - Neural Computing and Applications, 2023 - Springer
Breast cancer, which is also the leading cause of death among women, is one of the most
common forms of the disease that affects females all over the world. The discovery of breast …

[PDF][PDF] Multi-Objective Feature Selection Method by Using ACO with PSO Algorithm for Breast Cancer Detection.

R Saturi, P Premchand - International Journal of Intelligent Engineering & …, 2021 - inass.org
Breast cancer is the second most cause of cancer deaths in women after lung cancer, and
the treatment and diagnosis of breast cancer at an earlier stage is an important requirement …

Learning features using an optimized artificial neural network for breast cancer diagnosis

I AlShourbaji, P Kachare, W Zogaan… - SN Computer …, 2022 - Springer
Breast cancer (BC) has been one of the significant causes of death worldwide, and its early
detection can play a vital role in increasing the survival rate of this disease. This paper …

A combined parallel genetic algorithm and support vector machine model for breast cancer detection

H Xu, T Chen, J Lv, J Guo - Journal of Computational Methods …, 2016 - content.iospress.com
The serial genetic algorithms (SGAs) have been widely applied in improving support vector
machine (SVM) performance (eg, classification accuracy), and these hybrid SGA-SVM …

A hybrid data mining classifier for breast cancer prediction

H Asri, H Mousannif, H Al Moatassim - Advanced Intelligent Systems for …, 2020 - Springer
Classification and data mining methods are an effective way to classify data, especially in
medical field, where those methods are widely used in diagnosis and analysis to make …

Breast cancer detection using optimization-based feature pruning and classification algorithms

S Raiesdana - Middle East Journal of Cancer, 2021 - mejc.sums.ac.ir
Background: Early and accurate detection of breast cancer reduces the mortality rate of
breast cancer patients. Decision-making systems based on machine learning and intelligent …

A structured combination of ensemble classifier and filter-based feature selection to improve breast cancer diagnosis

D Zheng, P Tang, D Lu, L Han, S Saberi - Journal of Cancer Research and …, 2023 - Springer
Introduction Advances in technology have led to the emergence of computerized diagnostic
systems as intelligent medical assistants. Machine learning approaches cannot replace …