Deep Learning Algorithms for Predicting Breslow Thickness from Dermoscopic Images of Acral Lentiginous Melanomas.

Chu, Yu Seong; Lee, Solam; Lee, Sang Gyun; Chung, Kee Yang; Roh, Mi Ryung; Yang, Sejung; Oh, Byungho

Chu, Yu Seong; Lee, Solam; Lee, Sang Gyun; Chung, Kee Yang; Roh, Mi Ryung; Yang, Sejung; Oh, Byungho.

Afiliación

Chu YS; Department of Biomedical Engineering, Yonsei University, Wonju, Korea.
Lee S; Department of Dermatology, Yonsei University Wonju College of Medicine, Wonju, Korea.
Lee SG; Department of Dermatology, Gangnam Severance Hospital, Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Korea.
Chung KY; Department of Dermatology, Severance Hospital, Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Korea.
Roh MR; Department of Dermatology, Gangnam Severance Hospital, Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Korea.
Yang S; Department of Biomedical Engineering, Yonsei University, Wonju, Korea.
Oh B; Department of Dermatology, Severance Hospital, Cutaneous Biology Research Institute, Yonsei University College of Medicine, Seoul, Korea. Electronic address: obh505@gmail.com.

J Invest Dermatol ; 142(8): 2268-2271.e2, 2022 08.

Article en En | MEDLINE | ID: mdl-35032502

Asunto(s)

Aprendizaje Profundo; Melanoma; Neoplasias Cutáneas; Humanos; Melanoma/diagnóstico por imagen; Estudios Retrospectivos; Neoplasias Cutáneas/diagnóstico por imagen; Melanoma Cutáneo Maligno

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Cutáneas / Aprendizaje Profundo / Melanoma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Invest Dermatol Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos

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