Role of Advanced Computation, Predictive Technologies, and Big Data Analytics in Food and Nutrition Research
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Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are promising tools that can be used to develop algorithms to better understand and predict interactions between food- and nutrition-related data and health outcomes. Understanding that additional research is needed to identify areas where AI/ML is likely to have an impact, the National Academies Food and Nutrition Board hosted a public workshop in October 2023 to explore the future benefits and limitations of integrating big data and AI/ML tools into nutrition research. Participants also discussed issues related to diversity, equity, inclusion, bias, and privacy and the appropriate use of evidence generated from these new methods.
Table of Contents- Front Matter
- 1 Introduction
- 2 Setting the Stage
- 3 Applications and Lessons Learned
- 4 Capacity Building
- 5 Potential Applications of AI to Large-Scale Food and Nutrition Initiatives
- 6 Final Discussion and Synthesis
- References
- Appendix A: Workshop Agenda
- Appendix B: Biographical Sketches of the Speakers and Moderators