A Comprehensive Review of Breast Cancer Detection Using Machine Learning and Deep Learning Classifiers
Abishajey JB, Dharma Raj T, Nisha Evangelin L · 2024
Breast cancer is the major critical disease and suffered many people around the world. Recent progress in Machine Learning (ML) and Deep Learning (DL) techniques has established as valuable tools in breast cancer detection, enhancing both precision and effectiveness. This paper contribute a comprehensive review of breast cancer prediction utilize ML algorithms and DL model. ML is frequently employed in classifying breast cancer pattern due to exhibiting a crucial feature detection from composite breast cancer datasets. ML techniques such as Random Forests (RF), K-Nearest Neighbors (KNN), Logistic Regression (LR) and Support Vector Machines (SVM) are evaluate to classify and predict breast cancer based on various features. DL techniques including, Artificial Neural Network (ANN), Generative Adversarial Networks (GANs), Convolutional Neural Networks (CNNs), models have extracting attribute from raw imaging data, autonomously learning and offering high accuracy and sensitivity. In this analyses determine the most effective method for handling large datasets while maintaining high prediction accuracy.