{"title":"验证基于人工智能的应用程序,以估算每日膳食中的营养成分。","authors":"Teruhiko Imamura, Nikhil Narang, Koichiro Kinugawa","doi":"10.1016/j.jjcc.2024.10.003","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>AI-based estimation of nutrient components had relatively good agreement with actually calculated values.</p>","PeriodicalId":15223,"journal":{"name":"Journal of cardiology","volume":" ","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Validation of artificial intelligence-based application to estimate nutrients in daily meals.\",\"authors\":\"Teruhiko Imamura, Nikhil Narang, Koichiro Kinugawa\",\"doi\":\"10.1016/j.jjcc.2024.10.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>AI-based estimation of nutrient components had relatively good agreement with actually calculated values.</p>\",\"PeriodicalId\":15223,\"journal\":{\"name\":\"Journal of cardiology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of cardiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jjcc.2024.10.003\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of cardiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jjcc.2024.10.003","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Validation of artificial intelligence-based application to estimate nutrients in daily meals.
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.
期刊介绍:
The official journal of the Japanese College of Cardiology is an international, English language, peer-reviewed journal publishing the latest findings in cardiovascular medicine. Journal of Cardiology (JC) aims to publish the highest-quality material covering original basic and clinical research on all aspects of cardiovascular disease. Topics covered include ischemic heart disease, cardiomyopathy, valvular heart disease, vascular disease, hypertension, arrhythmia, congenital heart disease, pharmacological and non-pharmacological treatment, new diagnostic techniques, and cardiovascular imaging. JC also publishes a selection of review articles, clinical trials, short communications, and important messages and letters to the editor.