Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey.

Journal: BMJ open

PMID: 40122556

Abstract

OBJECTIVES: This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data.

Authors

Angwach Abrham Asnake

Department of Epidemiology and Biostatistics, College of Health Sciences and Medicine, Wolaita Sodo University, Sodo, Ethiopia angwachabrham@gmail.com.
Beminate Lemma Seifu

Public Health, Samara University, Semera, Ethiopia.
Alemayehu Kasu Gebrehana

Midwifery, Salale University, Collage of Health Science, Fitche, Ethiopia.

Keywords

Algorithms Bayes Theorem Cross-Sectional Studies Female Health Surveys Humans Infant Logistic Models Machine Learning Male Supervised Machine Learning Tanzania Vaccination

External Resources

View on PubMed Access via DOI PubMed (40122556)

Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey.

Abstract

Authors

Keywords

External Resources

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