NUTRIC AI: an AI-Assisted Personalized Nutrition Recommendation System

In this paper, NUTRIC AI is explained as a cutting-edge AI-assisted personal nutrition advisory system that provides personalized dietary guidelines through the review of individual clinical histories, current medical records, and AI-assisted meal planning. Real-time food recognition is performed by the system via Convolutional Neural Networks (CNNs), and Forecasting of Dietary Patterns is achieved using Long Short-Term Memory (LSTM) networks on past records of health information. Generative Networks are utilized to design personalized meal plans as per the specified dietary needs. For transparency and user confidence induction, the system utilizes Explainable AI (XAI) techniques, i.e., SHAP, to incorporate interpretability in its recommendations. Experimental trials depict substantial gains at a 95% accurate meal planning rate and a 92% user acceptance rate, better than existing available nutrition management platforms. The real-time food scoring system, user-specific dietary advice tailored to a user's own health record, and AI-facilitated chatbot interface are the distinguishing strengths of NUTRIC AI. The convergence of these three features places NUTRIC AI at the forefront of the art of personalized nutritional management.

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Publication Details

Published
2025-06-05
DOI
https://doi.org/10.1109/iccsp64183.2025.11089427
Citations
1
Primary Topic
Nutrition, Genetics, and Disease
Type
article
Field-Weighted Citation Impact
1.82
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article

NUTRIC AI: an AI-Assisted Personalized Nutrition Recommendation System

G Sandhiya, N Harish, S. Kavitha
1 citations
Nutrition, Genetics, and Disease
1.82
article

NUTRIC AI: an AI-Assisted Personalized Nutrition Recommendation System

G Sandhiya, N Harish, S. Kavitha
article en
1 citations

Abstract

In this paper, NUTRIC AI is explained as a cutting-edge AI-assisted personal nutrition advisory system that provides personalized dietary guidelines through the review of individual clinical histories, current medical records, and AI-assisted meal planning. Real-time food recognition is performed by the system via Convolutional Neural Networks (CNNs), and Forecasting of Dietary Patterns is achieved using Long Short-Term Memory (LSTM) networks on past records of health information. Generative Networks are utilized to design personalized meal plans as per the specified dietary needs. For transparency and user confidence induction, the system utilizes Explainable AI (XAI) techniques, i.e., SHAP, to incorporate interpretability in its recommendations. Experimental trials depict substantial gains at a 95% accurate meal planning rate and a 92% user acceptance rate, better than existing available nutrition management platforms. The real-time food scoring system, user-specific dietary advice tailored to a user's own health record, and AI-facilitated chatbot interface are the distinguishing strengths of NUTRIC AI. The convergence of these three features places NUTRIC AI at the forefront of the art of personalized nutritional management.

Artificial Intelligence in Medicine (Canada) (CA)
Zero hunger
Openalex Percentile: Top 13%
Nutrition, Genetics, and Disease
1.82
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