Singh, Utkarsh and Ahuja, Laxmi (2025) ML-Powered Nutrient Recommendations: A MERN Stack-Based Approach. International Journal of Innovative Science and Research Technology, 10 (5): 25may1102. pp. 1640-1657. ISSN 2456-2165

[thumbnail of IJISRT25MAY1102.pdf] Text
IJISRT25MAY1102.pdf - Published Version

Download (1MB)

Abstract

Personalized nutrition has become essential for both prevention and overall health in this day and age, too. However, the effectiveness of current dietary recommendation systems in satisfying a variety of user needs is limited by their frequent lack of scalability, interactivity, and adaptability. An ML-powered nutrient recommendation system built with MERN (MongoDB, Express.js, React.js, and Node.js) stack offers a novel solution to these problems in this paper. To personalize dietary advice, the proposed system mixes specific information provided directly by users with algorithms trained on huge databases of nutrition prepared using very sophisticated machine learning algorithms.

Item Type: Article
Subjects: L Education > L Education (General)
Divisions: Faculty of Law, Arts and Social Sciences > School of Education
Depositing User: Editor IJISRT Publication
Date Deposited: 10 Jun 2025 07:24
Last Modified: 10 Jun 2025 07:24
URI: https://eprint.ijisrt.org/id/eprint/1114

Actions (login required)

View Item
View Item