Design and Implementation of a Secure Patient–Doctor Triage Platform

Himaja Kaishetty (Northwest Missouri State University), Vamshi Krishna Balupari (Northwest Missouri State University), Tharun Guda (Northwest Missouri State University), Viswas Setty (Northwest Missouri State University)

Timely assessment of symptom severity continues to be a major challenge in healthcare, often resulting in delayed treatment for critical cases and inefficient use of clinical resources for non-urgent conditions. This paper presents EdgeCare Triage, an artificial intelligence (AI)–driven web and mobile application designed to assist with preliminary health assessments through secure, edge-based computation. The application allows patients to submit symptom details along with optional medical images, which are analyzed using on-device AI models to deliver real-time severity assessments and suggested next steps. These AI-generated triage results are then made accessible to doctors through a role-based web portal, where clinicians can review, annotate, and override recommendations as needed to ensure medical accuracy and reliability. The proposed system architecture follows a layered approach that includes client interfaces, an AI triage layer, Representational State Transfer (REST) full application services, and a secure data persistence layer. Key non-functional requirements—such as data privacy, security, scalability, and usability—are addressed through encrypted communication, role-based access control, audit logging, and robust session management mechanisms. Experimental prototypes demonstrate that the system effectively supports early clinical decision-making, reduces unnecessary hospital visits, and improves overall patient flow, all while maintaining strict privacy controls and compliance with healthcare standards.