Comparative Study on Machine Learning Algorithms in Early Prediction of Breast Cancer in Mammogram Image Datasets
Subash Chandra Bose Jaganathan, Veerasamy Murugesh, Balraj Dhakar · Apple Academic Press eBooks · 2025
Improving patient outcomes requires early diagnosis of breast cancer, and machine learning (ML) has become a potent tool for mammography image analysis. In order to identify breast cancer early, this research compares many machine learning (ML) techniques, such as Support Vector Machines (SVM), Convolutional Neural Networks (CNN), Random Forest, and k-Nearest Neighbors (k-NN). Accuracy, sensitivity, and specificity criteria are used to assess these algorithms’ performance on publicly accessible mammography datasets. The findings show that CNNs and other deep learning-based techniques perform better than conventional techniques in feature extraction and classification. This research emphasizes how crucial machine learning is to enhancing the detection of breast cancer.