Customized Recipes aligned with health needs using LLM

With the increasing focus on personalized healthcare and dietary needs, this paper discusses an AI-powered solution that generates recipes based on users' individual health conditions. Leveraging the Meta LLaMA 3 model, the system offers a unique approach to nutrition by using the health data to provide tailored recipe recommendations that align with medical guidelines. The core of the paper involves using advanced natural language processing (NLP) techniques to process user inputs such as medical information (e.g., from medical certificates or test reports). The model generates recipes that not only suit the user’s tastes but also adjust for dietary restrictions or health conditions like diabetes, hypertension, or allergies. By integrating these factors, the system creates nutritionally balanced meal plans that are personalized to the user's health profile. The primary objectives are to develop a robust recipe generation system that adapts to dynamic user inputs and health considerations and to design an intuitive interface for seamless interaction. Users will be able to provide health documents, and the AI will generate recipes that fulfill dietary preferences and adhere to specific health needs. This model will serve as a tool for users to make informed decisions about their nutrition and contribute to healthier lifestyles.

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Published
2025-04-24
DOI
https://doi.org/10.1109/iccies63851.2025.11032472
Primary Topic
Edcuational Technology Systems
Type
article
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0.00
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article

Customized Recipes aligned with health needs using LLM

P. Vijayalakshmi, C O Avina, N Arul Anand, S A Aryaa et al.
Edcuational Technology Systems
article

Customized Recipes aligned with health needs using LLM

P. Vijayalakshmi, C O Avina, N Arul Anand, S A Aryaa, I Alfina, G Subhashini
article en

Abstract

With the increasing focus on personalized healthcare and dietary needs, this paper discusses an AI-powered solution that generates recipes based on users' individual health conditions. Leveraging the Meta LLaMA 3 model, the system offers a unique approach to nutrition by using the health data to provide tailored recipe recommendations that align with medical guidelines. The core of the paper involves using advanced natural language processing (NLP) techniques to process user inputs such as medical information (e.g., from medical certificates or test reports). The model generates recipes that not only suit the user’s tastes but also adjust for dietary restrictions or health conditions like diabetes, hypertension, or allergies. By integrating these factors, the system creates nutritionally balanced meal plans that are personalized to the user's health profile. The primary objectives are to develop a robust recipe generation system that adapts to dynamic user inputs and health considerations and to design an intuitive interface for seamless interaction. Users will be able to provide health documents, and the AI will generate recipes that fulfill dietary preferences and adhere to specific health needs. This model will serve as a tool for users to make informed decisions about their nutrition and contribute to healthier lifestyles.

PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN)
Zero hunger
Openalex Percentile: Top 93%
Edcuational Technology Systems
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Customized Recipes aligned with health needs using LLM — P. Vijayalakshmi, C O Avina, et al. · (2025) | TGRS Research Map | TGRS