⚡ Quick Summary
This scoping review highlights the rapid expansion of artificial intelligence (AI) in the field of precision nutrition, revealing that approximately 75% of relevant studies have been published since 2020. The review emphasizes the importance of integrating minority and cultural factors to enhance health technologies and promote equity in nutrition.
🔍 Key Details
- 📊 Dataset: 198 articles extracted from major databases
- 🧩 Focus areas: Diet-related diseases, health optimization, disease prevention
- ⚙️ Methodology: PRISMA-ScR process for scoping reviews
- 🏆 Publication surge: ~75% of studies published since 2020
🔑 Key Takeaways
- 📈 AI’s role in precision nutrition is rapidly evolving, with significant research growth.
- 🍏 Focus on diseases such as diabetes and cardiovascular conditions is prevalent.
- 🔍 Methodologies and evaluation metrics are diverse, guiding future research.
- 🌍 Minority and cultural factors are crucial for advancing health technologies.
- 🚀 Future research should deepen the integration of these factors to maximize AI’s potential.
- 📚 Gaps and challenges in current studies highlight areas for further exploration.
- 💡 This review expands the understanding of AI’s impact on precision nutrition.
📚 Background
The intersection of artificial intelligence and nutrition is becoming increasingly significant as researchers seek to tailor dietary recommendations to individual needs. With the rise of AI technologies, there is a growing demand for comprehensive reviews that assess current research trends and identify future directions in this promising field.
🗒️ Study
This scoping review was conducted by a team of researchers who meticulously followed the PRISMA-ScR guidelines to analyze 198 articles related to AI and precision nutrition. The study aimed to map the current landscape of research, focusing on publication venues, targeted diseases, and the methodologies employed in these studies.
📈 Results
The findings reveal a remarkable increase in AI-driven precision nutrition research, with around 75% of the articles published since 2020. The studies predominantly address diet-related diseases, emphasizing health optimization and disease management. The review also highlights the diversity of datasets and critically evaluates the methodologies and metrics used, providing a roadmap for future investigations.
🌍 Impact and Implications
The implications of this review are profound. By recognizing the importance of minority and cultural factors, researchers can enhance the effectiveness of health technologies and promote equity in nutrition. This approach not only broadens the scope of AI applications in precision nutrition but also paves the way for more inclusive and effective health interventions.
🔮 Conclusion
This scoping review underscores the transformative potential of artificial intelligence in the realm of precision nutrition. By addressing existing gaps and challenges, the research community can harness AI’s capabilities to improve dietary recommendations and health outcomes. The future of nutrition science looks promising, and continued exploration in this field is essential for advancing public health.
💬 Your comments
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A Scoping Review of Artificial Intelligence for Precision Nutrition.
Abstract
BACKGROUND: With the role of artificial intelligence (AI) in precision nutrition rapidly expanding, a scoping review on recent studies and potential future directions is demanded.
OBJECTIVE: This scoping review examines: (1) the current landscape, including publication venues, targeted diseases, AI applications, methods, evaluation metrics, and considerations of minority and cultural factors; (2) common patterns in AI-driven precision nutrition studies; and (3) gaps, challenges and future research directions.
METHODS: Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) process, we extracted 198 articles from major databases with search keywords in three categories: precision nutrition keywords, artificial intelligence keywords and natural language processing keywords.
RESULTS: The extracted literature reveals a surge in AI-driven precision nutrition research, with ∼75% (n=148) published since 2020. It also showcases a diverse publication landscape, with these studies predominantly focusing on diet-related diseases, such as diabetes and cardiovascular conditions, while emphasizing health optimization, disease prevention, and management. We highlight diverse datasets and critically discuss methodologies and evaluation metrics to guide future studies. Importantly, we underscore the significance of minority and cultural aspects in enhancing health technologies and advancing equity. Future research should deepen the integration of these factors to fully harness AI’s potential in precision nutrition.
STATEMENT OF SIGNIFICANCE: This scoping review offers the most recent advancements in artificial intelligence for precision nutrition studies, expanding the scope to not only AI methodologies and their applications but also evaluates publication venues, targeted disease, datasets used and minority and cultural factors, which have been mostly overlooked in prior studies. Furthermore, with numerous gaps and challenges presented in the discussion section, this review significantly improves the understanding of AI’s role in precision nutrition and provides new insights for future research.
Author: [‘Wu X’, ‘Oniani D’, ‘Shao Z’, ‘Arciero P’, ‘Sivarajkumar S’, ‘Hilsman J’, ‘Mohr AE’, ‘Ibe S’, ‘Moharir M’, ‘Li LJ’, ‘Jain R’, ‘Chen J’, ‘Wang Y’]
Journal: Adv Nutr
Citation: Wu X, et al. A Scoping Review of Artificial Intelligence for Precision Nutrition. A Scoping Review of Artificial Intelligence for Precision Nutrition. 2025; (unknown volume):100398. doi: 10.1016/j.advnut.2025.100398