Validation of artificial intelligence-based application to estimate nutrients in daily meals

Teruhiko Imamura*, Nikhil Narang, Koichiro Kinugawa

*この論文の責任著者

研究成果: ジャーナルへの寄稿Letter査読

抄録

Background: Diet modification is a mainstay for the successful management of metabolic syndrome and potentially may reduce the risk of cardiovascular disease. Accurate estimation of essential nutrients in daily meals is currently challenging to quantify. HAKARIUM (AstraZeneca Co., Ltd., Osaka, Japan) is a recently introduced artificial intelligence (AI)-based application that can estimate each nutrient component through photographs, although its applicability to real-world practice remains unknown. Methods: Lunchtime meals served for healthy individuals at a single university cooperative society between September 2023 and February 2024 were analyzed. Nutrient components, including energy in the form of calories, protein, and salts, were estimated by the HAKARIUM application and compared with the actual nutrient values that were officially calculated and presented by the university cooperative society. Results: A total of 62 meals were included. Actual values of energy, protein, and salt content per meal were 382 (358, 431) kcal, 17.1 (13.9, 18.9) g, and 2.9 (2.6, 3.1) g, respectively. AI-estimated values of energy, protein, and salt content per meal were 636 (493, 835) kcal, 25.7 (19.7, 36.3) g, and 4.2 (3.5, 4.6) g, respectively. Most of the values were within the limits of agreement with significant correlations between the two variables, respectively (r > 0.80, p < 0.05 for all). Conclusion: AI-based estimation of nutrient components had relatively good agreement with actually calculated values.

本文言語英語
ページ(範囲)424-425
ページ数2
ジャーナルJournal of Cardiology
85
5
DOI
出版ステータス出版済み - 2025/05

ASJC Scopus 主題領域

  • 循環器および心血管医学

フィンガープリント

「Validation of artificial intelligence-based application to estimate nutrients in daily meals」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル