PERSONALIZED MEAL PLANNING APPLICATION BASED ON USER MEDICAL DAT

Dietary management plays a crucial role in preventing and managing chronic health conditions such as diabetes,cardiovascular diseases, and obesity. However, many individuals struggle to adhere to optimal meal plans due to a lackof personalized guidance tailored to their unique dietary needs and medical conditions. This challenge is particularlypronounced in regions with limited access to professional nutritionists. To address this issue, we developed an AI-drivenPersonalized Meal Planning Application that provides customized meal recommendations based on user-specific medicaldata and dietary preferences. Our approach integrates machine learning algorithms with a PostgreSQL database to analyzenutritional requirements and generate optimized meal plans. The system leverages TensorFlow-based models for dietarypattern recognition and React.js for an intuitive user interface, ensuring seamless interaction. By incorporating role-basedaccess control and secure authentication, the platform ensures data security while enhancing user experience. Theproposed solution offers a scalable, efficient, and user-friendly approach to personalized nutrition, ultimately improvingadherence to healthy eating habits and supporting better health outcomes.