This call for proposals seeks research projects that develop and utilize artificial intelligence (AI) and other computer-aided approaches to facilitate precision nutrition. Precision nutrition is an emerging field that aims to provide targeted dietary and nutritional recommendations for individuals with different characteristics and circumstances in order to prevent and treat diseases, and improve overall health and wellbeing. The Oxford Dictionary defines AI as the theory and development of computer systems that can perform tasks that typically require human intelligence processes. This article in Medpage Today covered how AI and other computer-aided approaches can transform precision nutrition by elucidating the complex factors and processes between an individual’s genetics, biology, behavior, social context and environment and their short and longer-term nutritional health outcomes. A January 2021 National Institutes of Health (NIH) workshop entitled “Precision Nutrition: Research Gaps and Opportunities” covered how our society is at a key inflection point, with technology, such as wearables and smartphones, allowing for much more information and data to be collected, and the potential for AI to utilize this data and information to inform precision nutrition efforts. For more details on precision nutrition and AI please see the National Academies of Sciences, Engineering and Medicine (NASEM) session on Challenges and Opportunities for Precision and Personalized Nutrition which covered current research design and methodologies, limitations in design and data, innovative methodologies and technologies at the various scales of precision nutrition (including genetic, physiological, individual, and social-ecological), the challenges of adapting technologies for utilization and policy and regulatory challenges, with perspectives from academia, federal government, and industry.
Examples of AI approaches include machine learning, including neural networks, cluster analysis, and natural language processing, systems modeling, and algorithm development. Potential applications to precision nutrition include the use of these methods to collect, store, analyze, or communicate nutrition and health-related data, or to develop representations of systems to investigate relationships between nutrition and health outcomes. This call for proposals seeks research projects that develop and utilize artificial intelligence (AI) and other computer-aided approaches to do the following:
Novel collection of nutrition and related health data. Example: Detecting eating episodes by tracking jawbone movements with a wearable sensor. https://doi.org/10.1145/3191736
Store, manage, and transform nutrition and health-related data. Example: Natural language processing to analyze free form text responses to a survey in order to quantify how participants felt the American public viewed people with obesity. https://doi.org/10.1002/oby.23037
Identify potential trends, associations, patterns, and relationships. Example: Machine learning algorithm to identify meals and food intake from body-worn sensor data, such as from motion sensing or continuous glucose monitoring. https://proceedings.mlr.press/v106/mirtchouk19a.html
Develop and utilize algorithms and representations that connect different food, drink, and nutrients with various health outcomes. Example: “Virtual Infant” model demonstrated how following formula feeding guidelines can impact infants’ weight. https://doi.org/10.1038/s41390-020-0844-3
Develop and utilize algorithms and representations that represent and predict different food and drink consumption behaviors. Examples: A model representing 3 cities, and their populations, homes, schools, and food and beverages sources to determine the impact of sugar sweetened beverage warning labels. https://doi.org/10.1016/j.amepre.2017.11.003; A study examines obesity-related behaviors within adolescent friendship networks, because adolescent peers have been identified as being important determinants of many health behaviors. https://doi.org/10.1016/j.socnet.2009.09.001
Visualize and communicate nutrition and health related data and information Example: Interactive platforms integrating data portals and visualization dashboards to accelerate data literacy and communication. https://doi.org/10.1093/advances/nmac022
Note that examples above are not exhaustive as there are a range of other possible computer-based approaches that would be responsive to this call. As this is intended to be a Pilot Program, the proposed project should be a gateway to a larger project (e.g., Research Project Grant [R01], Career Development [K] award).
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