Your browser doesn't support javascript.
loading
Skin Cancer Detection Using Deep Learning-A Review.
Naqvi, Maryam; Gilani, Syed Qasim; Syed, Tehreem; Marques, Oge; Kim, Hee-Cheol.
Afiliación
  • Naqvi M; Institute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea.
  • Gilani SQ; Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA.
  • Syed T; Department of Electrical Engineering and Computer Engineering, Technische Universität Dresden, 01069 Dresden, Germany.
  • Marques O; Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA.
  • Kim HC; Institute of Digital Anti-Aging Healthcare, Inje University, Gimhae 50834, Republic of Korea.
Diagnostics (Basel) ; 13(11)2023 May 30.
Article en En | MEDLINE | ID: mdl-37296763
Skin cancer is one the most dangerous types of cancer and is one of the primary causes of death worldwide. The number of deaths can be reduced if skin cancer is diagnosed early. Skin cancer is mostly diagnosed using visual inspection, which is less accurate. Deep-learning-based methods have been proposed to assist dermatologists in the early and accurate diagnosis of skin cancers. This survey reviewed the most recent research articles on skin cancer classification using deep learning methods. We also provided an overview of the most common deep-learning models and datasets used for skin cancer classification.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Diagnostics (Basel) Año: 2023 Tipo del documento: Article Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Diagnostics (Basel) Año: 2023 Tipo del documento: Article Pais de publicación: Suiza