Using One-Shot Prompting of Non-Fine-Tuned Commercial Artificial Intelligence to Assess Nutrients from Photographs of Japanese Meals

The simplest use of current AI via one-shot prompting and no fine-tuning accurately assesses fiber content in meals but is inaccurate for other nutritional parameters.

Authors

Toshimasa Yamauchi (ORCID: https://orcid.org/0000-0003-4827-6404)
Masaomi Nangaku (ORCID: https://orcid.org/0000-0001-7401-2934)
Kazuhiko Ohe (ORCID: https://orcid.org/0000-0002-4296-9536)
Y. Y. Ji (ORCID: https://orcid.org/0009-0003-2123-6311)
Kayo Waki (ORCID: https://orcid.org/0000-0003-0046-2523)

Institutions

The University of Tokyo (JP)

Publication Details

Journal: Journal of Diabetes Science and Technology
Published: 2025-01-10
DOI: https://doi.org/10.1177/19322968241309889
Citations: 1
Primary Topic: Nutritional Studies and Diet
Type: article
Field-Weighted Citation Impact: 1.88

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article

Using One-Shot Prompting of Non-Fine-Tuned Commercial Artificial Intelligence to Assess Nutrients from Photographs of Japanese Meals

Toshimasa Yamauchi, Masaomi Nangaku, Kazuhiko Ohe, Y. Y. Ji et al.

Jan 10, 2025

1 citations

Journal of Diabetes Science and Technology

Nutritional Studies and Diet

1.88

article

Using One-Shot Prompting of Non-Fine-Tuned Commercial Artificial Intelligence to Assess Nutrients from Photographs of Japanese Meals

Toshimasa Yamauchi, Masaomi Nangaku, Kazuhiko Ohe, Y. Y. Ji, Kayo Waki

January 10, 2025article en

1 citations

Abstract

The simplest use of current AI via one-shot prompting and no fine-tuning accurately assesses fiber content in meals but is inaccurate for other nutritional parameters.

Journal of Diabetes Science and Technology

The University of Tokyo (JP)

Zero hunger

Openalex Percentile: Top 20%

Nutritional Studies and Diet

1.88

DOI Open Access PDF OpenAlex

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