Identifying Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa Using Machine Learning: Cross-Sectional Study
Improving education and awareness, expanding access to screening (especially in rural areas), leveraging both digital health and community-based outreach, integrating screening with other health services, and addressing socioeconomic barriers are recommended strategies to increase cervical cancer screening rates in sub-Saharan Africa.
Authors
- Lemlem Daniel Baffa (ORCID: https://orcid.org/0000-0002-2291-7755)
- Tewodros Getaneh Alemu (ORCID: https://orcid.org/0000-0002-7829-0648)
- Gebrie Getu Alemu (ORCID: https://orcid.org/0009-0007-9451-2128)
- Habtamu Wagnew Abuhay (ORCID: https://orcid.org/0000-0001-9538-7612)
- Addisu Mesfin (ORCID: https://orcid.org/0000-0003-0076-4185)
- Muluken Chanie Agimas (ORCID: https://orcid.org/0000-0003-0808-124X)
- Nebebe Demis Baykemagn (ORCID: https://orcid.org/0009-0008-9403-6915)
- Dagnew Getnet Adugna (ORCID: https://orcid.org/0000-0002-3670-4953)
- Mekuriaw Nibret Aweke (ORCID: https://orcid.org/0000-0002-7152-6435)
- Alemu Teshale Bicha
Institutions
- University of Gondar (ET)
Publication Details
- Journal
- JMIR Public Health and Surveillance
- Published
- 2025-06-06
- DOI
- https://doi.org/10.2196/71677
- Citations
- 2
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 4.96