This paper is in the following e-collection/theme issue:

Public Health Informatics (138) Public (e)Health, Digital Epidemiology and Public Health Informatics (1032) mHealth for Screening (299) Innovations and Technology for Cancer Prevention and Screening (205) Patient Education for Cancer (231) Machine Learning (2138) Obstetrics, Gynecology, and Reproductive Medicine (335) Behavioural Surveillance for Public Health (296)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71677, first published .
Identifying Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa Using Machine Learning: Cross-Sectional Study

Identifying Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa Using Machine Learning: Cross-Sectional Study

Identifying Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa Using Machine Learning: Cross-Sectional Study

Authors of this article:

Nebebe Demis Baykemagn1 Author Orcid Image ;   Mekuriaw Nibret Aweke2 Author Orcid Image ;   Amare Mesfin2 Author Orcid Image ;   Lemlem Daniel Baffa2 Author Orcid Image ;   Muluken Chanie Agimas3 Author Orcid Image ;   Habtamu Wagnew Abuhay3 Author Orcid Image ;   Dagnew Getnet Adugna4 Author Orcid Image ;   Tewodros Getaneh Alemu5 Author Orcid Image ;   Alemu Teshale Bicha6 Author Orcid Image ;   Gebrie Getu Alemu3 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Nwokedi V, Nwajiugo G, Okechukwu O, Biose R, Motilewa O, Anosike W, Adetona O. Prevalence and Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa: A Systematic Review and Meta-Analysis. Oncology, Nuclear Medicine and Transplantology 2025;1(2):onmt009 View
  2. Tanveer A, Ali R, Majhi J, Mukherjee M. Predicting and identifying correlates of inequalities in breast cancer screening uptake using national level data from India. Frontiers in Artificial Intelligence 2026;8 View