Liquid-Based Oral Brush Cytology: Evaluation of Two Artificial Intelligence Models in Papanicolaou and Silver-Stained Nucleolar Organizer Region Analyses
The AgNOR automated model is reliable when assessing NOR count in oral samples processed by different cytological methods, when compared to the human analysis. The Papanicolaou model still needs more training with LBOBC samples.
Authors
- Rebeca Carolina Campos de Almeida Silva (ORCID: https://orcid.org/0000-0001-7949-2957)
- Fernanda Visioli (ORCID: https://orcid.org/0000-0002-4033-8431)
- Manuel M. Oliveira (ORCID: https://orcid.org/0000-0003-4957-9984)
- Erick Souza Pedraça (ORCID: https://orcid.org/0000-0002-1037-0553)
- Giorgina Barbara Piccoli (ORCID: https://orcid.org/0000-0001-7203-1744)
- Tatiana Wannmacher Lepper (ORCID: https://orcid.org/0000-0001-7905-0737)
- Pantelis Varvaki Rados (ORCID: https://orcid.org/0000-0001-9307-1980)
- Natália Batista Daroit (ORCID: https://orcid.org/0000-0002-0764-8999)
- Igor Cavalcante Guedes (ORCID: https://orcid.org/0000-0003-4073-4159)
- Ana Laura Ferrares Espinosa (ORCID: https://orcid.org/0000-0003-0891-7043)
- Nathalia Baldicera Lopes
Institutions
- Universidade Federal do Rio Grande do Sul (BR)
Publication Details
- Journal
- Acta Cytologica
- Published
- 2025-11-21
- DOI
- https://doi.org/10.1159/000549618
- Primary Topic
- Oral Health Pathology and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00