The Role of Early Detection and Health Education in Breast Cancer Prevention: A Literature Review

Abstract

Breast cancer is one of the leading causes of death among women worldwide and poses a serious challenge in public health. Preventive efforts through early detection and health education are key strategies to reduce morbidity and mortality rates. This study is a literature review of five journals discussing the role of technology and educational interventions in breast cancer prevention. The method used is a narrative-descriptive approach by analyzing research findings from 2024–2025. The review results show that the application of machine learning and deep learning algorithms, such as Support Vector Machine (SVM), Logistic Regression, DenseNet, and Inception-ResNet-v2, can improve early detection accuracy to more than 90%. Meanwhile, health educationparticularly through training in breast self-examination (BSE) has proven effective in improving women’s knowledge, attitudes, and behaviors toward early breast cancer detection. The synergy between technology and health education has shown a significantly positive impact on breast cancer prevention efforts. Therefore, integrating these two approaches needs to be strengthened in national health policies to achieve sustainable, community-based early detection..