Machine vision model using nail images for non-invasive detection of iron deficiency anemia in university students
The DenseNet169-based model proved to be a promising tool for non-invasive detection of iron deficiency anemia, with potential for application in clinical and educational settings. Future improvements in preprocessing and dataset diversification could enhance performance and applicability.
Authors
- Jorge Raúl Navarro-Cabrera (ORCID: https://orcid.org/0000-0002-7369-4459)
- Miguel Angel Valles-Coral (ORCID: https://orcid.org/0000-0002-8806-2892)
- María Elena Farro-Roque
- Nelly Reátegui-Lozano
- Lolita Arévalo-Fasanando
Institutions
- Universidad Nacional de San Martín (PE)
Publication Details
- Journal
- Frontiers in Big Data
- Published
- 2025-04-09
- DOI
- https://doi.org/10.3389/fdata.2025.1557600
- Citations
- 5
- Primary Topic
- Traditional Chinese Medicine Studies
- Type
- article
- Field-Weighted Citation Impact
- 11.91
Funders
- Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica