NutriGuard: LLM-Driven Nutritional Assessment for Chronic Disease Prevention

This conference paper presents NutriGuard, an innovative system leveraging Large Language Models (LLMs) for comprehensive nutritional assessment aimed at preventing chronic diseases. The system analyzes dietary intake and health data to provide personalized recommendations and risk assessments, contributing significantly to the fields of Big Data, Artificial Intelligence, and Machine Learning.

Authors:

• Md Azizul Hakim (Student, Bangladesh Sweden Polytechnic Institute, Bangladesh)
• Rashedul Arefin Ifty (Undergraduate Teaching Assistant, International Islamic University Chittagong, Bangladesh) - Contact Author
• Khaled Eabne Delowar (Adjunct Lecturer, International Islamic University Chittagong, Bangladesh)
• Sazzad Hossen Chowdhury (Student, International Islamic University Chittagong, Bangladesh)
• Imdadur Rashid (Student, International Islamic University Chittagong, Bangladesh)
• Md Shakib (Graduate, International Islamic University Chittagong, Bangladesh)

Topics: Big Data, Artificial Intelligence & Machine Learning

Recommended citation: Hakim, M. A., Ifty, R. A., Delowar, K. E., Chowdhury, S. H., Rashid, I., & Shakib, M. (2025). "NutriGuard: LLM-Driven Nutritional Assessment for Chronic Disease Prevention." IEEE Conference Proceedings.