The Comprehensive College Health and Insurance Management System addresses the evolving needs of academic institutions by integrating cutting-edge technologies to prioritize the health and well-being of students and staff. This system includes modules for user authentication, health and lifestyle assessment, insurance prediction, continuous monitoring, and educational tools, all accessible through a user-friendly mobile or web application. The Health Prediction Module stands at the core utilizing advanced models for insurance risk assessment, providing tailored recommendations based on user-input health data, and enabling continuous monitoring for timely interventions.
The study and Development Module contributes to ongoing health research by anonymizing data, advancing predictive models, and aligning the system with emerging healthcare trends. The proposed system, anchored in advanced predictive health models, aims to empower users with personalized health insights while providing administrators with tools for risk assessment and proactive intervention.
The study delves into the architecture, methodologies, and mathematical foundations of the predictive health model, emphasizing its pivotal role in a comprehensive college management system. Leveraging data science and machine learning techniques, the model incorporates features such as multi-task learning, loss functions tailored for health prediction, risk classification, and lifestyle analysis. Privacy and security measures are prioritized, ensuring compliance with data protection regulations. The study concludes with results showcasing the model's accuracy and potential impact on student health and insurance management, marking this system as a pioneering solution for colleges prioritizing holistic well-being.