Dermatologist versus artificial intelligence confidence in dermoscopy diagnosis: Complementary information that may affect decision-making.

Van Molle, Pieter; Mylle, Sofie; Verbelen, Tim; De Boom, Cedric; Vankeirsbilck, Bert; Verhaeghe, Evelien; Dhoedt, Bart; Brochez, Lieve

Van Molle, Pieter; Mylle, Sofie; Verbelen, Tim; De Boom, Cedric; Vankeirsbilck, Bert; Verhaeghe, Evelien; Dhoedt, Bart; Brochez, Lieve.

Afiliação

Van Molle P; IDLab, Department of Information Technology, Ghent University-IMEC, Ghent, Belgium.
Mylle S; Department of Dermatology, Ghent University Hospital, Ghent, Belgium.
Verbelen T; Cancer Research Institute Ghent (CRIG), Ghent, Belgium.
De Boom C; IDLab, Department of Information Technology, Ghent University-IMEC, Ghent, Belgium.
Vankeirsbilck B; IDLab, Department of Information Technology, Ghent University-IMEC, Ghent, Belgium.
Verhaeghe E; IDLab, Department of Information Technology, Ghent University-IMEC, Ghent, Belgium.
Dhoedt B; Department of Dermatology, Ghent University Hospital, Ghent, Belgium.
Brochez L; IDLab, Department of Information Technology, Ghent University-IMEC, Ghent, Belgium.

Exp Dermatol ; 32(10): 1744-1751, 2023 10.

Article em En | MEDLINE | ID: mdl-37534916

Assuntos

Inteligência Artificial; Dermatologistas; Dermoscopia; Dermatopatias; Humanos; Dermoscopia/métodos; Melanoma/diagnóstico por imagem; Melanoma/patologia; Neoplasias Cutâneas/diagnóstico por imagem; Neoplasias Cutâneas/patologia; Dermatopatias/diagnóstico por imagem; Dermatopatias/patologia

Palavras-chave

computer vision; deep learning; neural networks; skin lesion classification; uncertainty

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Dermatopatias / Inteligência Artificial / Dermoscopia / Dermatologistas Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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