Artificial Intelligence Image-Diagnosis for Female Genital Schistosomiasis
This study highlights the potential of deep learning-based models for automated diagnosis for FGS while reducing the reliance on specialized clinical expertise. It also underscores the need for further work to address current limitations of such AI-based methods for FGS diagnosis.
Authors
- Mireille Gomes (ORCID: https://orcid.org/0000-0002-3348-908X)
- Julia Alison Noble (ORCID: https://orcid.org/0000-0002-3060-3772)
- Jiayuan Zhu (ORCID: https://orcid.org/0000-0002-3641-4489)
Institutions
- Merck KGaA, Darmstadt (Germany) (DE)
- University of Oxford (GB)
Publication Details
- Journal
- Mayo Clinic Proceedings Digital Health
- Published
- 2025-06-21
- DOI
- https://doi.org/10.1016/j.mcpdig.2025.100245
- Citations
- 2
- Primary Topic
- Parasites and Host Interactions
- Type
- article
- Field-Weighted Citation Impact
- 4.10
Funders
- Merck KGaA
- Engineering and Physical Sciences Research Council