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Predicting Off-Track Development in Infants Aged 0 to 6 Months in Low-Resource Settings Using Machine Learning

Domaine:

healthcare
Créateur:
BenOwiUZI
Éditeur:
Cen
Éditeur:
OSF
Hôte:avatar
This study used machine learning models to predict developmental delays among infants aged 0–6 months in Kilifi, Kenya. Using data from 1,995 infants, the models showed good performance and identified limited psychosocial stimulation and increasing age as key predictors. The findings highlight the potential of machine learning for early prediction and targeted interventions in low-resource settings.

Visit

doi.orgosf.io

Languages

Swahili, Coastal

Tags

Health Information TechnologyMaternal and Child HealthPhysical Sciences and MathematicsPublic HealthMedicine and Health SciencesDevelopmental PsychologyChild PsychologyComputer SciencesSocial and Behavioral SciencesPsychology+7

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