An Intelligent AI-Driven Framework for Automated Pediatric Immunization Scheduling and Infection Risk Surveillance

Timely pediatric immunization is a critical component of preventive healthcare. However, many healthcare institutions still rely on manual or semi-digital systems for vaccination tracking, leading to inefficiencies, missed schedules, and increased infection risks. This paper proposes an Intelligent AI-Driven Framework for Automated Pediatric Immunization Scheduling and Infection Risk Surveillance. The system is implemented as a web-based platform using Python, Django, and MySQL. It integrates predictive scheduling algorithms, role-based authentication, real-time hospital booking, and automated notification mechanisms. The framework aims to reduce manual workload, eliminate data redundancy, improve vaccination compliance, and provide infection risk insights. Experimental results demonstrate enhanced efficiency, faster retrieval, and improved system reliability compared to traditional manual systems.