Deep learning-based classification of dermatological lesions given a limited amount of labelled data.

Krammer, S; Li, Y; Jakob, N; Boehm, A S; Wolff, H; Tang, P; Lasser, T; French, L E; Hartmann, D

Krammer, S; Li, Y; Jakob, N; Boehm, A S; Wolff, H; Tang, P; Lasser, T; French, L E; Hartmann, D.

Afiliação

Krammer S; Department of Dermatology and Allergy, University Hospital, LMU Munich, Munich, Germany.
Li Y; Department of Dermatology and Allergy, University Hospital, LMU Munich, Munich, Germany.
Jakob N; Department of Dermatology and Allergy, University Hospital, LMU Munich, Munich, Germany.
Boehm AS; Department of Dermatology and Allergy, University Hospital, LMU Munich, Munich, Germany.
Wolff H; Department of Dermatology and Allergy, University Hospital, LMU Munich, Munich, Germany.
Tang P; Department of Informatics, School of Computations, Information, and Technology, and Munich Institute of Biomedical Engineering, Technical University of Munich, Munich, Germany.
Lasser T; Department of Informatics, School of Computations, Information, and Technology, and Munich Institute of Biomedical Engineering, Technical University of Munich, Munich, Germany.
French LE; Department of Dermatology and Allergy, University Hospital, LMU Munich, Munich, Germany.
Hartmann D; Department of Dermatology and Allergy, University Hospital, LMU Munich, Munich, Germany.

J Eur Acad Dermatol Venereol ; 36(12): 2516-2524, 2022 Dec.

Article em En | MEDLINE | ID: mdl-35876737

Assuntos

Inteligência Artificial; Aprendizado Profundo; Humanos; Pele

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Aprendizado Profundo Tipo de estudo: Screening_studies Limite: Humans Idioma: En Revista: J Eur Acad Dermatol Venereol Assunto da revista: DERMATOLOGIA / DOENCAS SEXUALMENTE TRANSMISSIVEIS Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha

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