Virtual Hospital Platform for Preventive Healthcare and Remote Consultation

Abstract

This paper discusses the creation and use of a Virtualized Multi-Role Hospital Care Platform that aims to fill the gap in preventative healthcare and remote medical consultation. Traditional healthcare systems sometimes have problems discovering chronic diseases early, managing them from a distance, and obtaining specialists to treat patients in remote areas. We recommend a full-stack solution that digitally copies hospital workflows for four primary roles: Patient, Doctor, Lab Assistant, and Admin. This will help fix these challenges. The platform combines four different Machine Learning (ML) models to predict diseases early and help individuals make decisions based on AI that can be explained. These models are mainly about assessing overall health, predicting skin cancer, predicting cardiovascular health, and prediciting the risk of liver cirrhosis. There are many layers of security in the system to keep private medical information safe. Security is enforced through CAPTCHA-verified login, JWT session management, OTP-gated patient record access. Telehealth consultations, digital lab report management, and real-time AI diagnostics all function together without any complications because they all use frontend and backend services. The findings of the model tests show that the platform might significantly lighten the load on healthcare infrastructure and enhance patient outcomes by allowing early intervention and remote access. They also show that the platform is quite good at making predictions.