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Evaluating the Generalisability of Region-naïve Machine Learning Algorithms for the Identification of Epilepsy in Low-resource Settings

dc.contributor.authorDuta I.
dc.contributor.authorKariuki S. M.
dc.contributor.authorNgugi A. K.
dc.contributor.authorMwesige A. K.
dc.contributor.authorMasanja H.
dc.contributor.authorMwanga D. M.
dc.contributor.author
dc.contributor.authorOwusu-Agyei S.
dc.contributor.author
dc.contributor.authorWagner R.
dc.contributor.author
dc.contributor.authorCross J. H.
dc.contributor.author
dc.contributor.authorSander J. W.
dc.contributor.author
dc.contributor.authorNewton C. R.
dc.contributor.author
dc.contributor.authorSen A.
dc.contributor.author
dc.contributor.author& Jones G. D
dc.contributor.author
dc.date.accessioned2025-07-24T07:23:19Z
dc.date.available2025-07-24T07:23:19Z
dc.date.issued2025
dc.identifier.urihttps://doi.org/10.1371/journal.pdig.0000491
dc.identifier.urihttp://knowhub.aphrc.org/handle/123456789/2402
dc.description.abstractThis pilot stepped-wedge cluster-randomized trial evaluated the effect of text message reminders on newborn vaccination timing in Nairobi slums. Pregnant women either received SMS prompts for birth-dose vaccines (oral polio and BCG) or usual care. Results showed significantly improved timely vaccination during the SMS intervention: oral polio (93.0% vs 80.9%) and BCG (92.7% vs 81.6%). Adjusted risk ratios confirmed the benefit of SMS reminders, demonstrating their potential to increase birth-dose vaccine coverage in resource-constrained settings.
dc.publisherPLOS (Public Library of Science)
dc.subjectmHealth II Vaccination Timeliness II SMS Reminders II Urban Health II Randomized Controlled Trial II Newborn Immunization II Public Health
dc.titleEvaluating the Generalisability of Region-naïve Machine Learning Algorithms for the Identification of Epilepsy in Low-resource Settings


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