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Evaluating of Machine Learning Models in Predicting COVID-19 Vaccine Uptake in Kenya

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Bibliographic Details
Published in:Journal of Kenya Association of Physicians
Format: Online Article RSS Article
Published: 2025
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container_title Journal of Kenya Association of Physicians
description
discipline_display African Open Access — Medical & Health Sciences
discipline_facet African Open Access — Medical & Health Sciences
format Online Article
RSS Article
genre Journal Article
id rss_article:86989
institution FRELIP
journal_source_facet Journal of Kenya Association of Physicians
publishDate 2025
publishDateSort 2025
record_format rss_article
spellingShingle Evaluating of Machine Learning Models in Predicting COVID-19 Vaccine Uptake in Kenya
African Open Access — Medical & Health Sciences
General
African Open Access — Medical & Health Sciences
sub_discipline_display General
sub_discipline_facet General
subject_display African Open Access — Medical & Health Sciences
General
African Open Access — Medical & Health Sciences
African Open Access — Medical & Health Sciences
General
African Open Access — Medical & Health Sciences
subject_facet African Open Access — Medical & Health Sciences
General
African Open Access — Medical & Health Sciences
title Evaluating of Machine Learning Models in Predicting COVID-19 Vaccine Uptake in Kenya
title_auth Evaluating of Machine Learning Models in Predicting COVID-19 Vaccine Uptake in Kenya
title_full Evaluating of Machine Learning Models in Predicting COVID-19 Vaccine Uptake in Kenya
title_fullStr Evaluating of Machine Learning Models in Predicting COVID-19 Vaccine Uptake in Kenya
title_full_unstemmed Evaluating of Machine Learning Models in Predicting COVID-19 Vaccine Uptake in Kenya
title_short Evaluating of Machine Learning Models in Predicting COVID-19 Vaccine Uptake in Kenya
title_sort evaluating of machine learning models in predicting covid-19 vaccine uptake in kenya
topic African Open Access — Medical & Health Sciences
General
African Open Access — Medical & Health Sciences
url https://kapjournal.com/index.php/kap/en/article/view/158