Author ORCID Identifier

Tsai - https://orcid.org/0000-0001-9188-0362

Document Type

Conference Proceeding

Publication Date

8-13-2024

Publication Title

New Trends in Disruptive Technologies, Tech Ethics, and Artificial Intelligence

First Page

85

Last Page

96

DOI

https://doi-org.leo.lib.unomaha.edu/10.1007/978-3-031-66635-3_8

Abstract

The importance of nutrition during pregnancy cannot be overstated, as it profoundly impacts maternal and fetal health outcomes. Optimal fetal growth and development are contingent upon adequate nutrition throughout gestation, which in turn requires that expectant mothers possess a high level of nutritional literacy. This latter factor may serve as a valuable predictor of pregnancy outcomes. This paper seeks to leverage the capabilities of a retrieval-augmented large language model to provide personalized prenatal nutrition guidance. We employed Meta’s LLAMA 2 model and integrated an expert-curated dataset of nutrition information. Our evaluation, conducted using ChatGPT-based metrics, revealed that while the augmented model did not yield significant improvements in overall response quality, it could generate more thoughtful and specific responses easily comprehensible to users. We conclude by discussing the challenges encountered and lessons learned from our investigation.

Comments

This version of the chapterhas been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-66635-3_7

Publisher holds a Bespoken License

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