Prediction of breast cancer, comparative review of machine learning techniques, and their analysis

N Fatima, L Liu, S Hong, H Ahmed - IEEE Access, 2020 - ieeexplore.ieee.org
Breast cancer is type of tumor that occurs in the tissues of the breast. It is most common type
of cancer found in women around the world and it is among the leading causes of deaths in …

A novel approach for breast cancer detection using optimized ensemble learning framework and XAI

RM Munshi, L Cascone, N Alturki, O Saidani… - Image and Vision …, 2024 - Elsevier
Breast cancer (BC) is a common and highly lethal ailment. It stands as the second leading
contributor to cancer-related deaths in women worldwide. The timely identification of this …

PCA-DNN: A Novel Deep Neural Network Oriented System for Breast Cancer Classification

P Rani, R Kumar, A Jain, R Lamba… - … on Pervasive Health …, 2023 - publications.eai.eu
INTRODUCTION: The number of women diagnosed with breast cancer has risen rapidly in
recent years all around the world, and this trend is anticipated to continue. After lung cancer …

Breast cancer detection using convoluted features and ensemble machine learning algorithm

M Umer, M Naveed, F Alrowais, A Ishaq, AA Hejaili… - Cancers, 2022 - mdpi.com
Simple Summary This paper presents a breast cancer detection approach where the
convoluted features from a convolutional neural network are utilized to train a machine …

Multispectral band selection and spatial characterization: Application to mitosis detection in breast cancer histopathology

H Irshad, A Gouaillard, L Roux, D Racoceanu - … Medical Imaging and …, 2014 - Elsevier
Breast cancer is the second most frequent cancer. The reference process for breast cancer
prognosis is Nottingham grading system. According to this system, mitosis detection is one …

Breast cancer detection employing stacked ensemble model with convolutional features

H Karamti, R Alharthi, M Umer, H Shaiba… - Cancer …, 2024 - journals.sagepub.com
Breast cancer is a major cause of female deaths, especially in underdeveloped countries. It
can be treated if diagnosed early and chances of survival are high if treated appropriately …

[PDF][PDF] Machine learning-based hybrid recommendation (SVOF-KNN) model for breast cancer coimbra dataset diagnosis

RK Barwal, N Raheja, M Bhiyana… - International Journal on …, 2023 - academia.edu
An effective way to identify breast cancer is by creating a prediction algorithm using risk
factors. Models for ML have been used to improve the effectiveness of early detection. This …

Hybridization of ML techniques for predicting Breast Cancer

M Jeeva, E Padmapriya, RG Rajan - 2022 Third International …, 2022 - ieeexplore.ieee.org
Breast cancer is one of the most prevalent forms of cancer among Indian residents. Breast
cancer ranks fourth in the top ten cancers in America. Every four minutes, a woman in India …

[HTML][HTML] Machine learning framework for breast cancer detection with feature selection with L2 ridge regularization: insights from multiple datasets

P Kandhasamy, DP Devi… - Journal of Translational …, 2025 - oaepublish.com
Aim: This study aims to investigate and apply effective machine learning techniques for the
early detection and precise diagnosis of breast cancer. The analysis is conducted using …

A New Approach of Optimizing Breast Cancer Diagnosis Through Genetic Algorithm-Based Feature Selection

FZ El-Hassani, NE Joudar, K Haddouch - … On Big Data and Internet of …, 2024 - Springer
Breast cancer presents a significant health challenge, necessitating intricate detection
methods. This study introduces a specialized 1D-Convolutional Neural Network for precise …