AI-POWERED PERSONAL HEALTH RECOMMENDATION SYSTEM

1. INTRODUCTION

Healthcare systems across the world are rapidly evolving with the integration of Artificial Intelligence (AI), Natural Language Processing (NLP), and Large Language Models (LLMs). Traditional healthcare systems mainly focus on diagnosis and treatment after the occurrence of diseases, while preventive healthcare and personalized recommendations remain limited. Most healthcare applications provide generalized advice that often ignores individual lifestyle habits, medical history, sleep patterns, fitness goals, and behavioural conditions. Recent advancements in Generative AI have enabled the development of intelligent healthcare systems capable of generating adaptive and context-aware recommendations. These systems can analyze user information such as age, Body Mass Index (BMI), sleep duration, lifestyle habits, physical activity levels, and existing medical conditions to provide personalized suggestions. The proposed AI-Powered Personal Health Recommendation System utilizes Generative AI APIs to generate personalized healthcare guidance dynamically. The system offers recommendations related to diet planning, exercise routines, sleep improvement, medication reminders, and preventive healthcare management. Unlike traditional machine learning approaches that require large datasets, feature engineering, and model training, the proposed framework leverages pretrained Large Language Models through prompt engineering techniques. The system is developed using modern web technologies including Next.js, React.js, Node.js, Express.js, Prisma ORM, PostgreSQL, and Gemini AI API. The framework improves accessibility to healthcare guidance, increases user engagement, and demonstrates the practical implementation of Generative AI in healthcare systems.