The art of diagnosing rare skin tumors: Can DL-CNNs enhance dermatologists’ diagnostic accuracy?
The tested DL-CNN showed a limited diagnostic performance in diagnosing RST. While minor effects on expert decision-making were observed, overall diagnostic accuracy remained highest with full clinical context. Better training data are needed for improved DL-CNN performance in RST.
Authors
- Alexander Enk (ORCID: https://orcid.org/0000-0002-1816-421X)
- Rainer Hofmann‐Wellenhof (ORCID: https://orcid.org/0000-0001-8688-3243)
- Philipp Tschandl (ORCID: https://orcid.org/0000-0003-0391-7810)
- Katharina Susanne Kommoss (ORCID: https://orcid.org/0000-0003-2428-2658)
- Rainer Hofmann‐Wellenhof (ORCID: https://orcid.org/0000-0001-8688-3243)
- Holger A. Haenssle (ORCID: https://orcid.org/0000-0001-7255-3104)
- Anastasia S. Vollmer (ORCID: https://orcid.org/0000-0003-4200-9647)
- Julia K. Winkler (ORCID: https://orcid.org/0000-0003-3197-9867)
- W Stolz
- Andreas Blum
- Teresa Kränke
Institutions
- Medical University of Graz (AT)
- Heidelberg University (DE)
- München Klinik (DE)
- Klinikum Konstanz (DE)
- Medical University of Vienna (AT)
Publication Details
- Journal
- European Journal of Cancer
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1016/j.ejca.2025.115751
- Citations
- 1
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.05