Article
DeepMetabolix: Intelligent Architecture for Cross-Sectional Dietary Optimization
Generalized health platforms fail to address individual metabolic differences and fitness goals. This paper presents DeepMetabolix, an AI-driven web-based system providing personalized diet and fitness recommendations. The system analyzes user parameters (age, gender, height, weight, activity level, fitness goals) to calculate BMI and daily caloric requirements using standard metabolic equations (Mifflin-St Jeor). An OpenRouter-based AI chatbot delivers adaptive, context-aware dietary guidance. Graphical visualization and historical tracking improve user engagement. Evaluation with 60 users over 4 weeks demonstrates 92% recommendation relevance, 88% dietary compliance improvement, and 4.4/5 user satisfaction. The system bridges conventional static fitness applications and intelligent personalized health management, offering a scalable solution for metabolic assessment and dietary optimization.
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