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		<Title>DeepMetabolix: Intelligent Architecture for Cross-Sectional Dietary Optimization</Title>
		<Author> Suravaram Venkatesh, Yerramsetti Madhu Kumar, Muddada Kishor, Palina Lingamurthy,  Dr. S. Mouli</Author>
		<Volume>03</Volume>
		<Issue>03</Issue>
		<Abstract>Generalized health platforms fail to address individual metabolic differences and fitness goals This paper presents DeepMetabolix an AIdriven webbased 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 MifflinSt Jeor An OpenRouterbased AI chatbot delivers adaptive contextaware 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 445 user satisfaction The system bridges conventional static fitness applications and intelligent personalized health management offering a scalable solution for metabolic assessment and dietary optimization</Abstract>
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<copyright-statement>Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved</copyright-statement>
<copyright-year>2026</copyright-year>
</permissions>
		</www.jsetms.com>
		