Predicting undernutrition among elementary schoolchildren in the Philippines using machine learning algorithms.

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Bibliographic Details
Title: Predicting undernutrition among elementary schoolchildren in the Philippines using machine learning algorithms.
Authors: Siy Van VT; Health Sciences Program, School of Science and Engineering, Ateneo de Manila University, Quezon City, Philippines. Electronic address: vsiyvan@ateneo.edu., Antonio VA; Department of Mathematics, School of Science and Engineering, Ateneo de Manila University, Quezon City, Philippines., Siguin CP; Community Welfare, Wellness, and Well-being Laboratory, Ateneo de Manila University, Quezon City, Philippines., Gordoncillo NP; Institute of Human Nutrition and Food, University of the Philippines Los Baños, Laguna, Philippines., Sescon JT; Department of Economics, Ateneo de Manila University, Quezon City, Philippines., Go CC; Department of Mathematics, School of Science and Engineering, Ateneo de Manila University, Quezon City, Philippines., Miro EP; Department of Mathematics, School of Science and Engineering, Ateneo de Manila University, Quezon City, Philippines.
Source: Nutrition (Burbank, Los Angeles County, Calif.) [Nutrition] 2022 Apr; Vol. 96, pp. 111571. Date of Electronic Publication: 2021 Dec 17.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Science Country of Publication: United States NLM ID: 8802712 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-1244 (Electronic) Linking ISSN: 08999007 NLM ISO Abbreviation: Nutrition Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1873-1244
DOI:10.1016/j.nut.2021.111571