Using Multiple Real-World Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning
Research output: Contribution to journal › Letter › Contributed › peer-review
Contributors
Details
Original language | English |
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Pages (from-to) | 1028-1031 |
Number of pages | 4 |
Journal | Journal of the American Academy of Dermatology |
Volume | 90 |
Issue number | 5 |
Publication status | Published - May 2024 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0003-4340-9706/work/152545758 |
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ORCID | /0000-0002-2164-4644/work/152545846 |
unpaywall | 10.1016/j.jaad.2023.11.065 |
Scopus | 85184078064 |
Mendeley | 4d305500-a5f4-3d26-8cf8-8213f7d093d3 |
Keywords
Keywords
- uncertainty estimation, deep learning, diagnostic accuracy, dermatology, robustness, diagnosis, melanoma, artificial intelligence, dermoscopy