Evaluation of Guidelines for Exposures to Technologically Enhanced Naturally Occurring Radioactive Materials

Evaluation of Guidelines for Exposures to Technologically Enhanced Naturally Occurring Radioactive Materials

  • Éditeur: National Academies Press
  • ISBN: 9780309062978
  • eISBN Pdf: 9780309580700
  • eISBN Epub: 9780309183994
  • Lieu de publication:  United States
  • Année de publication électronique: 2024
  • Mois : Avril
  • Pages: 129
  • Langue: Anglais

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.

  • Cover
  • 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

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