What is in a food store name? Leveraging large language models to enhance food environment data.

Journal: Frontiers in artificial intelligence
Published Date:

Abstract

INTRODUCTION: It is not uncommon to repurpose administrative food data to create food environment datasets in the health department and research settings; however, the available administrative data are rarely categorized in a way that supports meaningful insight or action, and ground-truthing or manually reviewing an entire city or neighborhood is rate-limiting to essential operations and analysis. We show that such categorizations should be viewed as a classification problem well addressed by recent advances in natural language processing and deep learning-with the advent of large language models (LLMs).

Authors

  • Analee J Etheredge
    Center for Population Health Data Science, NYC Department of Health and Mental Hygiene, New York City, NY, United States.
  • Samuel Hosmer
    Center for Population Health Data Science, NYC Department of Health and Mental Hygiene, New York City, NY, United States.
  • Aldo Crossa
    Center for Population Health Data Science, NYC Department of Health and Mental Hygiene, New York City, NY, United States.
  • Rachel Suss
    Center for Population Health Data Science, NYC Department of Health and Mental Hygiene, New York City, NY, United States.
  • Mark Torrey
    Center for Population Health Data Science, NYC Department of Health and Mental Hygiene, New York City, NY, United States.

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