Unveiling Breast Cancer Risk Profiles: A Comprehensive Survival Clustering Analysis Empowered by an Online Web Application for Personalized Medicine

Abstract

AbstractOnline tools, such as web-based applications, aid medical doctors in recommending treatments and conducting thorough patient profile investigations. Prior studies have created web-based survival analysis tools for cancer survival. However, these often offer basic features and simplistic models, providing shallow data insights. Our research involves an in-depth risk profile analysis using survival clustering on real-world data. We’ve developed a user-friendly Shiny application to simplify the use of our findings. By utilizing survival clustering, we uncover distinct subgroups and unique risk profiles among breast cancer patients. Our online app empowers researchers and clinicians to explore and gain insights into breast cancer risk profiles, enhancing personalized medicine and clinical decision-making.