Breast cancer remains a significant global health concern, affecting millions of women each year. Early detection and risk assessment are critical factors in improving outcomes and reducing mortality rates. In response to this challenge, this study presents the development of a mobile application designed to assess an individual's risk of developing breast cancer. The mobile application leverages state-of-the-art machine learning algorithms and integrates them with user-friendly interfaces to provide a seamless and accessible platform for risk assessment. Users input personal and family medical history, lifestyle factors, and genetic information, if available, into the application. The system then processes this data to calculate an individual's risk of developing breast cancer, offering a personalized assessment.

Breast Cancer, Early detection, Artificial Intelligence, Mobile Application