Automated assessment of skin histological tissue structures by artificial intelligence in cutaneous melanoma
The developed applications demonstrated high performance, enhancing the analysis of time-consuming histological features. The model facilitates the identification of histopathological features in large datasets allowing potential refinement of melanoma staging.
Authors
- Tamar E. C. Nijsten (ORCID: https://orcid.org/0000-0001-9940-2875)
- Sjors A. Koppes (ORCID: https://orcid.org/0000-0002-8833-531X)
- Antien L. Mooyaart (ORCID: https://orcid.org/0000-0001-9810-5780)
- Loes M. Hollestein (ORCID: https://orcid.org/0000-0001-8922-6791)
- Alex L. Nigg
- Thamila Kerkour (ORCID: https://orcid.org/0000-0002-5857-1792)
- Yunlei Li (ORCID: https://orcid.org/0000-0002-5697-1602)
Institutions
- Erasmus MC (NL)
- Erasmus University Rotterdam (NL)
Publication Details
- Journal
- Pathology - Research and Practice
- Published
- 2025-03-29
- DOI
- https://doi.org/10.1016/j.prp.2025.155923
- Citations
- 1
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.05
Funders
- KWF Kankerbestrijding