A low-cost platform for automated cervical cytology: addressing health and socioeconomic challenges in low-resource settings
The results indicate that MobileNet might be a suitable model for real-world deployment on the low-cost platform, offering high precision and efficiency in classifying cervical cytology images. This system presents a first step towards a promising solution for improving cervical cancer screening in low-resource settings.
Authors
- César Antonio Irecta-Nájera (ORCID: https://orcid.org/0000-0001-9914-1230)
- Héctor Ochoa‐Díaz‐López (ORCID: https://orcid.org/0000-0002-8421-4983)
- Xariss M. Sánchez‐Chino (ORCID: https://orcid.org/0000-0002-8599-8150)
- José Ocampo-López-Escalera (ORCID: https://orcid.org/0000-0002-6927-1891)
- Saúl D. Tobar-Alas
- Martha Rosete-Aguilar
Institutions
- Mexican Social Security Institute (MX)
- Hospital General De Zona (MX)
- Departamento de Salud (ES)
- El Colegio de la Frontera Sur (MX)
- Universidad Nacional Autónoma de México (MX)
Publication Details
- Journal
- Frontiers in Medical Technology
- Published
- 2025-03-31
- DOI
- https://doi.org/10.3389/fmedt.2025.1531817
- Citations
- 4
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 9.92