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In Journal of the European Academy of Dermatology and Venereology : JEADV

Machine learning (ML) models for skin cancer recognition have reported comparable or superior performance to dermatologists in controlled or restricted settings.1 One restriction is the number of disease classes. When trained models are deployed into real-world contexts, an important challenge will be the detection of rare but aggressive skin cancers that are not well-covered in training datasets, such as Merkel cell carcinoma (MCC) and amelanotic melanoma.

Steele L, Velazquez-Pimentel D, Thomas B R


Amelanotic, Artificial Intelligence, Machine Learning, Melanoma, Mobile Applications, Reproducibility of Results, Skin Neoplasms