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MRI India Journals Vol. 9 No. 10 (2025): Volume 9 Issue 10 2025

Survey on Vital : A Smart Supplement and Nutrition Recommendation System

Authors

  • Anmol Budhewar Assistant Professor- Dept. of Computer Engineering, SITRC Nashik
  • Pratik Shinde B.E – Dept of Computer Engineering, SITRC Nashik
  • Om Sonawane B.E – Dept of Computer Engineering, SITRC Nashik
  • Ankit Patil B.E – Dept of Computer Engineering, SITRC Nashik
  • Pankaj Binnar B.E – Dept of Computer Engineering, SITRC Nashik

DOI:

https://doi.org/10.65521/ijasret.v9i10.1491

Keywords:

Smart Supplement Recommendation Nutrition Advice System Machine Learning and NLP Prescription Analysis (OCR) Personalized Healthcare Platform

Abstract

This paper presents Vital – a Smart Supplement and Nutrition Recommendation System, a web-based platform which is designed to provide personalised supplement recommendations and nutrition advice. To analyse user profiles and medical prescriptions, the system uses machine learning (ML), natural language processing (NLP), and optical character recognition (OCR). The user is able to input details such as age, gender, allergies, and health goals to get supplement suggestions that fit their needs. If a user uploads a prescription, the system checks it to find the medicines, connects them to health conditions, and creates nutrition advice using external APIs. The platform displays a full-stack implementation using React.js, Node.js, Python-based ML services, mongoDB which is combined with datasets and external APIs. Vital combines healthcare data and smart recommendation models to help people make correct health decisions. At the same time, it highlights the importance of consulting medical professionals before taking any supplements or medications.

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Published

2025-10-30

How to Cite

Budhewar, A., Shinde, P., Sonawane, O., Patil, A., & Binnar, P. (2025). Survey on Vital : A Smart Supplement and Nutrition Recommendation System. International Journal of Advanced Scientific Research and Engineering Trends, 9(10), 25–27. https://doi.org/10.65521/ijasret.v9i10.1491

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