Evaluation of the applicability of immunohistochemical expression of Ki-67 as a prognostic factor in cutaneous melanoma
Conclusions: XAI integration in dermatology enhances diagnostic accuracy and clinician trust.Certified devices with XAI functionalities improve workflows by making AI predictions more transparent.However, real-world validation and developer transparency remain essential.Clinician feedback is crucial to ensure AI tools are reliable and interpretable. 2 [2] Future advancements in multimodal XAI as in the ongoing Intelligent Total Body Scanner for Early Detection of Melanoma project (iToBoS) pave the way for better XAI integration in dermatology.Figure 2. Multimodal data integration for holistic risk scoring in skin cancer detection Anonymized metadata (demographics, history, genetics) is combined with TBP and dermoscopic images in the AI dataset.The algorithm generates holistic risk scores for both patients and lesions, supporting personalized diagnostics.
Authors
- Eduardo Bertolli (ORCID: https://orcid.org/0000-0003-1412-0436)
- João Pedreira Duprat Neto (ORCID: https://orcid.org/0000-0001-8968-4506)
- C. Pinto (ORCID: https://orcid.org/0009-0001-9233-4715)
- Livia Prôa Felippe (ORCID: https://orcid.org/0000-0003-4682-4534)
- B.D. Assis
- Mel Lobo
- V.C. Siervi
- R. Nahime
Institutions
- Escola Bahiana de Medicina e Saúde Pública (BR)
- AC Camargo Hospital (BR)
- Beneficência Portuguesa de São Paulo (BR)
Publication Details
- Journal
- EJC Skin Cancer
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.ejcskn.2025.100438
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00