دورية أكاديمية
أعرض في EDS

An Innovative Machine Learning Approach to Predict the Dietary Fiber Content of Packaged Foods.

التفاصيل البيبلوغرافية
العنوان: An Innovative Machine Learning Approach to Predict the Dietary Fiber Content of Packaged Foods.
المؤلفون: Davies T; The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW 2042, Australia., Louie JCY; The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW 2042, Australia.; School of Biological Science, Faculty of Science, The University of Hong Kong, Hong Kong 999077, China., Scapin T; The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW 2042, Australia.; Nutrition in Foodservice Research Centre, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil., Pettigrew S; The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW 2042, Australia., Wu JH; The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW 2042, Australia., Marklund M; The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW 2042, Australia.; Department of Epidemiology, John Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.; Department of Public Health and Caring Sciences, Uppsala University, 75122 Uppsala, Sweden., Coyle DH; The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW 2042, Australia.
المصدر: Nutrients [Nutrients] 2021 Sep 14; Vol. 13 (9). Date of Electronic Publication: 2021 Sep 14.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Publishing Country of Publication: Switzerland NLM ID: 101521595 Publication Model: Electronic Cited Medium: Internet ISSN: 2072-6643 (Electronic) Linking ISSN: 20726643 NLM ISO Abbreviation: Nutrients Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI Publishing
مواضيع طبية MeSH: Energy Intake* , Food Labeling* , Food Packaging* , Machine Learning* , Nutritive Value*, Dietary Fiber/*analysis , Food Analysis/*methods, Algorithms ; Australia ; Automation ; Beverages/analysis ; Diet ; Fast Foods/analysis ; Feeding Behavior ; Humans ; Nutrients ; Nutrition Policy ; Nutritional Status
مستخلص: Underconsumption of dietary fiber is prevalent worldwide and is associated with multiple adverse health conditions. Despite the importance of fiber, the labeling of fiber content on packaged foods and beverages is voluntary in most countries, making it challenging for consumers and policy makers to monitor fiber consumption. Here, we developed a machine learning approach for automated and systematic prediction of fiber content using nutrient information commonly available on packaged products. An Australian packaged food dataset with known fiber content information was divided into training ( n = 8986) and test datasets ( n = 2455). Utilization of a k-nearest neighbors machine learning algorithm explained a greater proportion of variance in fiber content than an existing manual fiber prediction approach ( R 2 = 0.84 vs. R 2 = 0.68). Our findings highlight the opportunity to use machine learning to efficiently predict the fiber content of packaged products on a large scale.
References: Nutrients. 2018 May 11;10(5):. (PMID: 29751656)
Arq Gastroenterol. 2020 Apr-Jun;57(2):144-149. (PMID: 32609155)
Nutrients. 2020 Aug 16;12(8):. (PMID: 32824342)
Prev Med Rep. 2018 Sep 24;12:198-202. (PMID: 30364851)
Comput Biol Med. 2021 May;132:104320. (PMID: 33735760)
Food Res Int. 2021 Jun;144:110329. (PMID: 34053533)
Nutrients. 2018 May 31;10(6):. (PMID: 29857517)
Nutrients. 2019 Jul 22;11(7):. (PMID: 31336626)
PLoS Med. 2012;9(6):e1001235. (PMID: 22745605)
J Am Board Fam Med. 2012 Jan-Feb;25(1):16-23. (PMID: 22218620)
Open Access Maced J Med Sci. 2019 May 30;7(10):1723-1727. (PMID: 31210830)
J Acad Nutr Diet. 2012 May;112(5):642-8. (PMID: 22709768)
JMIR Mhealth Uhealth. 2014 Aug 21;2(3):e37. (PMID: 25147135)
Nutrients. 2021 May 31;13(6):. (PMID: 34072684)
J Chiropr Med. 2018 Mar;17(1):44-53. (PMID: 29628808)
J Food Compost Anal. 2015 Nov 1;43:7-17. (PMID: 26273127)
Nutrition. 2020 Oct;78:110861. (PMID: 32592978)
J Acad Nutr Diet. 2015 Nov;115(11):1861-70. (PMID: 26514720)
Eur J Clin Nutr. 2014 May;68(5):619-22. (PMID: 24619105)
Eur J Prev Cardiol. 2012 Dec;19(6):1326-32. (PMID: 21971487)
Nutrients. 2019 Dec 13;11(12):. (PMID: 31847188)
Philos Trans R Soc Lond B Biol Sci. 2010 Sep 27;365(1554):2793-807. (PMID: 20713385)
J Chiropr Med. 2017 Dec;16(4):289-299. (PMID: 29276461)
Nutr Res Rev. 2017 Dec;30(2):149-190. (PMID: 28676135)
Science. 2015 Jul 17;349(6245):255-60. (PMID: 26185243)
Public Health Nutr. 2009 May;12(5):729-31. (PMID: 19366466)
Biology (Basel). 2020 Oct 06;9(10):. (PMID: 33036150)
فهرسة مساهمة: Keywords: computer science; dietary fiber; machine learning; public health
المشرفين على المادة: 0 (Dietary Fiber)
تواريخ الأحداث: Date Created: 20210928 Date Completed: 20211111 Latest Revision: 20211111
رمز التحديث: 20240829
مُعرف محوري في PubMed: PMC8470168
DOI: 10.3390/nu13093195
PMID: 34579072
قاعدة البيانات: MEDLINE
الوصف
تدمد:2072-6643
DOI:10.3390/nu13093195