About this Research Topic
In the era of rapid technological advancement, the integration of artificial intelligence (AI) with clinical nutrition, chronic disease management, nutritional intervention, and health management is revolutionizing the field of human health. This interdisciplinary approach holds immense potential for developing personalized nutrition plans tailored to individual health needs, which were previously unattainable. Despite the promising outlook, significant challenges persist, particularly in the complexity of data collection and the need for algorithms that ensure both accuracy and reliability. Recent studies have demonstrated the potential of AI in predicting individual nutritional requirements and managing chronic diseases, yet the field is still in its nascent stages. Current research is addressing these challenges through innovative methodologies, but there remains a critical need for further investigation to refine these technologies and fully realize their potential in improving public health outcomes.
This research topic aims to establish a prominent platform at the intersection of Clinical Nutrition, Artificial Intelligence, Chronic Disease Management, Nutritional Intervention, and Health Management. We aim to address current challenges in applying AI to personalized dietary planning and management of chronic diseases. By introducing the latest technologies and methodologies, we seek to foster a more precise understanding of individual nutritional needs. Through collaboration between academic and industry experts, our objective is to accelerate innovation in the fields of nutrition and artificial intelligence. Ultimately, we aim to deliver more intelligent and personalized solutions for managing chronic diseases and improving overall health and quality of life on a global scale.
To gather further insights in the integration of AI and nutrition, we welcome articles addressing, but not limited to, the following themes:
- Clinical Nutrition Assessment and Customized Dietary Plans: Including research on individual nutrition requirement prediction based on artificial intelligence, dietary habit analysis, and customized dietary recommendations.
- Chronic Disease Management and Preventive Nutrition: Research on the application of artificial intelligence in chronic disease prevention, health management, and nutritional interventions, including predictive models based on big data and machine learning.
- Clinical Nutrition and Artificial Intelligence: Exploring the integration of artificial intelligence in clinical nutrition research, including predictive modeling, personalized dietary recommendations, and innovative approaches for health management.
- Nutritional Intervention in Biological and Metabolic Regulation: Exploring research on artificial intelligence in nutritional biology, metabolic regulation, and the interaction between nutrition and genetics to promote the development of personalized nutrition.
- Intelligent Dietary Assistance Tools and Applications: Developing and evaluating AI-based nutrition management software, intelligent dietary assistance tools, and mobile applications to promote healthy eating and lifestyle.
This research topic aims to establish a prominent platform at the intersection of Clinical Nutrition, Artificial Intelligence, Chronic Disease Management, Nutritional Intervention, and Health Management. We aim to address current challenges in applying AI to personalized dietary planning and management of chronic diseases. By introducing the latest technologies and methodologies, we seek to foster a more precise understanding of individual nutritional needs. Through collaboration between academic and industry experts, our objective is to accelerate innovation in the fields of nutrition and artificial intelligence. Ultimately, we aim to deliver more intelligent and personalized solutions for managing chronic diseases and improving overall health and quality of life on a global scale.
To gather further insights in the integration of AI and nutrition, we welcome articles addressing, but not limited to, the following themes:
- Clinical Nutrition Assessment and Customized Dietary Plans: Including research on individual nutrition requirement prediction based on artificial intelligence, dietary habit analysis, and customized dietary recommendations.
- Chronic Disease Management and Preventive Nutrition: Research on the application of artificial intelligence in chronic disease prevention, health management, and nutritional interventions, including predictive models based on big data and machine learning.
- Clinical Nutrition and Artificial Intelligence: Exploring the integration of artificial intelligence in clinical nutrition research, including predictive modeling, personalized dietary recommendations, and innovative approaches for health management.
- Nutritional Intervention in Biological and Metabolic Regulation: Exploring research on artificial intelligence in nutritional biology, metabolic regulation, and the interaction between nutrition and genetics to promote the development of personalized nutrition.
- Intelligent Dietary Assistance Tools and Applications: Developing and evaluating AI-based nutrition management software, intelligent dietary assistance tools, and mobile applications to promote healthy eating and lifestyle.
Keywords: Clinical Nutrition, Artificial Intelligence, Chronic Disease Management, Nutritional Intervention, Health Management
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
