Integrating generative AI with ABCDE rule analysis for enhanced skin cancer diagnosis, dermatologist training and patient education
The achieved simulations of potential lesion progressions could facilitate improved early detection and understanding of how lesions evolve. By combining the optical flow analysis with the established criteria of the ABCDE rule, this study presents a significant advancement in dermatoscopic diagnostics and patient education. Future research will focus on applying this integrated approach to real patient data, with the aim of enhancing the understanding of lesion progression and the personalization of dermatological care.
Authors
- Bernhard Roth (ORCID: https://orcid.org/0000-0001-9389-7125)
- Rafael García (ORCID: https://orcid.org/0000-0002-1681-6229)
- Josep Quintana (ORCID: https://orcid.org/0000-0003-3577-2011)
- Sandra González-Villà (ORCID: https://orcid.org/0000-0002-5393-1664)
- Lennart Jütte (ORCID: https://orcid.org/0000-0002-5564-7472)
- Martin Steven
Institutions
- Leibniz University Hannover (DE)
- Universitat de Girona (ES)
- Clínica Girona (ES)
- Hospital Quirónsalud Sagrado Corazón (ES)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2024-10-03
- DOI
- https://doi.org/10.3389/fmed.2024.1445318
- Citations
- 11
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 3.11
Funders
- European Commission
- Deutsche Forschungsgemeinschaft