A Path Towards Personalized Smart Nutrition
A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrition and Public Health".
Deadline for manuscript submissions: 25 February 2025 | Viewed by 37
Special Issue Editor
Interests: nutritional and metabolic diseases; healthy lifestyle; obesity prevention and management; stress-induced eating behavior; emerging technologies in diet-related disease management
Special Issue Information
Dear Colleagues,
The rising demand for personalized nutrition needs innovative approaches to ensure accessibility, accuracy, and effectiveness for a diverse population. Personalized smart nutrition is a tailored approach to dietary planning and management utilizing advanced technology, data analytics, and artificial intelligence (AI) to create individualized nutrition plans. This concept combines insights from various sources, such as genetic data, metabolic profiles, lifestyle habits, and health goals, to recommend optimal dietary choices for an individual. Additionally, it requires robust infrastructure for data privacy and security and collaboration among healthcare providers, nutrition experts, and tech companies to deliver comprehensive and user-friendly solutions. Possible innovative solutions include 1. genetic and biomarker analysis; 2. metabolic profiling, 3. data-driven recommendations; 4. behavioral insights; and 5. continuous monitoring and feedback. The tools and technologies involved are wearable devices (track physical activity, heart rate, and other vital statistics), mobile apps (assist with food logging, and nutrient tracking, and provide real-time recommendations), AI and machine learning (analyze large datasets to deliver personalized nutrition advice), and genomic testing kits (provide insights into how an individual’s DNA influences their nutritional needs).
Prof. Dr. Veronica Mocanu
Guest Editor
Manuscript Submission Information
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Keywords
- personalized smart nutrition
- personalized diet plan
- nutrient monitoring
- remote health monitoring systems
- wearable devices
- mobile apps
- virtual reality
- genomic testing
- metabolic profiling
- AI and machine learning
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