Computational Strategies in Nutrigenetics: Constructing a Reference Dataset of Nutrition-Associated Genetic Polymorphisms https://doi.org/10.1101/2023.08.04.23293659
-
Updated
Mar 6, 2025 - Jupyter Notebook
Computational Strategies in Nutrigenetics: Constructing a Reference Dataset of Nutrition-Associated Genetic Polymorphisms https://doi.org/10.1101/2023.08.04.23293659
The AI4Food-NuritionFW framework facilitates the creation of food image datasets tailored to configurable eating behaviours. User-friendly and accessible to all.
Graph-based RAG system for biomedical nutrigenetic knowledge discovery. Enables natural language queries on gene-nutrient interactions, supports personalized nutrition counseling, and runs 100% locally with Ollama LLMs and SBERT embeddings.
The "Nutritionist-Generative-AI-Doctor-using-Google-Gemini-Pro-Vision" project leverages Google Gemini Pro Vision to create an AI-driven nutritionist and doctor that offers personalized health advice. It uses generative AI to analyze user data and provide tailored recommendations for diet and well-being.
Add a description, image, and links to the personalized-nutrition topic page so that developers can more easily learn about it.
To associate your repository with the personalized-nutrition topic, visit your repo's landing page and select "manage topics."