Pulmoviral Atrophy Syndrome (PAS) Assessment & Prediction System

Abstract

Pulmoviral Antrophy Syndrome (PAS) is a progressive respiratory condition that requires timely assessment, continuous monitoring, and effective patient guidance to improve healthcare outcomes. This paper presents a web-based PAS Early Diagnosis and Monitoring System designed to support risk evaluation, disease progression prediction, CT scan analysis, and patient health management through an integrated digital platform. The proposed system is developed using React and TypeScript and incorporates modules for PAS risk assessment, predictive analytics, research visualization, and an AI-powered health assistant. Patient assessment results, prediction records, CT analysis findings, and conversational interactions are securely managed through a local storage framework, enabling longitudinal tracking and monitoring. Interactive dashboards and analytical visualizations provide healthcare insights through risk trends, prediction history, and performance metrics. Additionally, the AI assistant delivers educational guidance related to lifestyle modifications, respiratory health, exercise, and dietary recommendations. The modular architecture enhances usability, accessibility, and scalability while promoting informed decision-making. The proposed platform demonstrates the potential of integrating predictive healthcare technologies, intelligent assistance, and data visualization techniques to support early detection and continuous management of PAS in a user-friendly environment.