Intelligent Decision Support System for Health Monitoring and Personalized Recommendations Using AI and Machine Learning

Abstract

he rapid growth of chronic diseases such as diabetes, hypertension, thyroid disorders, and obesity has created a demand for intelligent healthcare monitoring systems. As described in the uploaded abstract (), this research proposes an Intelligent Decision Support System (IDSS) designed to assist users in monitoring health parameters and receiving personalized recommendations through a web-based platform. The system integrates Machine Learning (ML), Natural Language Processing (NLP), and data analytics to analyze user inputs such as BMI, dietary habits, and activity levels. It provides real-time health insights, reminders, and chatbot-based assistance. The architecture utilizes modern web technologies including React.js, Flask, and MySQL to ensure scalability and efficiency. Experimental results demonstrate improved user engagement, accuracy in recommendations, and enhanced health awareness. This system contributes to digital healthcare by offering a cost-effective, accessible, and intelligent solution for continuous health monitoring and lifestyle management.