AI Driven Healthcare Recommendation System
DOI:
https://doi.org/10.47392/IRJAEH.2026.0223Keywords:
Disease Prediction, Symptoms, Health Management, Machine Learning, Preventive Care, AI in Healthcare, Healthcare Recommend-er System, Natural Language Processing (NLP), Symptom Analysis, Personalized Health Recommendations, Medical Chat-bot, Speech-to-Text, Cloud Deployment, Healthcare AI Assistant, Preventive Healthcare, User-Concentric AI, Medical Data Analysis, Health Monitoring, Web-Based Healthcare SolutionsAbstract
In today's rapidly changing world and evolving healthcare , Driven healthcare recommendation systems have emerged as trans formative tools for personalized and efficient medical guidance. This project helps us to identify the healthcare issues and aims to develop an AI-powered Healthcare Recommneder that provides tailored health recommendations based on user input, medical history, and symptoms. Is is all about utilizing Machine Learning(ML),Natural Language Processing (NLP), the system analyzes user queries and suggests potential diagnoses, lifestyle modifications, and preventive measures. The System integrates a knowledge -based model ,real time medical data. The recommend-er system uses a knowledge-based model, real-time medical data, and symptom-checking algorithms to improve accuracy.It uses speech-to-text capabilities for seamless voice interaction and stores chat history for continuity. The user-friendly interface, developed with Bootstrap/Tailwind CSS, ensures accessibility across devices. Deployed on cloud platforms like Render, Vermicelli, or AWS, this AI-driven approach empowers users with timely, data-driven recommendations, contributing to proactive health management and early disease detection.
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Copyright (c) 2026 International Research Journal on Advanced Engineering Hub (IRJAEH)

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