Forecasting acute childhood malnutrition in Kenya using machine learning and diverse sets of indicators.

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Bibliographic Details
Title: Forecasting acute childhood malnutrition in Kenya using machine learning and diverse sets of indicators.
Authors: Tadesse GA; Microsoft AI for Good Research Lab, Nairobi, Kenya., Ferguson L; University of Southern California, Institute on Inequalities in Global Health, Los Angeles, California, United States of America.; Amref International University, Nairobi, Kenya., Robinson C; Microsoft AI for Good Research Lab, Redmond, Washington, United States of America., Kuria S; Amref Health Africa, Nairobi, Kenya., Wanyonyi H; Amref Health Africa, Nairobi, Kenya., Murage S; Division of Nutrition and Dietetics, Ministry of Health, Nairobi, Kenya., Mburu S; Amref Health Africa, Nairobi, Kenya., Dodhia R; Microsoft AI for Good Research Lab, Redmond, Washington, United States of America., Lavista Ferres JM; Microsoft AI for Good Research Lab, Redmond, Washington, United States of America., Dilkina B; University of Southern California, Center for AI in Society, Los Angeles, California, United States of America.
Source: PloS one [PLoS One] 2025 May 14; Vol. 20 (5), pp. e0322959. Date of Electronic Publication: 2025 May 14 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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