A Benchmark for Automatic Visual Classification of Clinical Skin Disease Images
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Several algorithms incorporating artificial intelligence have been developed to help interpret clinical and dermoscopic images for a variety of skin conditions.
“Several algorithms incorporating artificial intelligence (AI) have been developed to help interpret both clinical11,12,13,14,15 and dermoscopic16,17,18,19,20,21,22,23 images for a variety of skin conditions”
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References 45 · Cited by 197
- Authors
- Sun, X., Yang, J., Sun, M., & Wang, K.
- Affiliations
- Nankai University (CN)
- Corresponding author
- Yang, Jufeng
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 206-222
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2519210008
- Cited by
- 197
- References
- 45
- Citations by year
- 2026: 7 · 2025: 25 · 2024: 24 · 2023: 28 · 2022: 41 · 2021: 32 · 2020: 17 · 2019: 13 · 2018: 8 · 2017: 1 · 2016: 1
- FWCI
- 23.89
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- skin disease classification, benchmark dataset, dermatological image analysis, convolutional neural networks, computer-aided diagnosis, skin lesion recognition
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