Machine learning-enhanced modeling approach for optimally predicting household level food insecurity in Ethiopia during COVID-19

Abstract Food insecurity remains a critical global challenge, with low-income countries such as Ethiopia bearing a disproportionate burden. In settings where frequent data collection is limited, developing predictive models provides a cost-effective means of anticipating risks to enhance rapid life-...

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Principais autores:	Henok Wariso Waqo, Gezahegn Mekonnen Woldemedihn, Yehenew Getachew Kifle, Frank Konietschke, Zeytu Gashaw Asfaw
Formato:	Artigo
Idioma:	Inglês
Publicado:	Nature Portfolio 2026-05-01
Series:	Scientific Reports
Assuntos:	Food insecurity COVID-19 ML-models Prediction Regularization Validation
Acceso en liña:	https://doi.org/10.1038/s41598-026-53425-3
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