Predicting risk of inadequate micronutrient intake with transferable machine learning models

Abstract Identifying populations at risk of inadequate micronutrient intake is necessary for governments and development partners in low- and middle-income countries to make informed and timely decisions on nutrition-relevant policies and programmes. In this study, we propose a machine learning meth...

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Principais autores:	Vasiliki Voukelatou, Kevin Tang, Ilaria Lauzana, Manita Jangid, Giulia Martini, Saskia de Pee, Frances Knight, Duccio Piovani
Format:	Artigo
Jezik:	Inglês
Izdano:	Nature Portfolio 2026-01-01
Serija:	Scientific Reports
Teme:	Nutrition Policy Classification Machine learning Data science for social good
Online dostop:	https://doi.org/10.1038/s41598-025-26179-7
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