Accuracy of a smartphone application for triage of skin lesions based on machine learning algorithms.

Udrea, A; Mitra, G D; Costea, D; Noels, E C; Wakkee, M; Siegel, D M; de Carvalho, T M; Nijsten, T E C

Udrea, A; Mitra, G D; Costea, D; Noels, E C; Wakkee, M; Siegel, D M; de Carvalho, T M; Nijsten, T E C.

Affiliation

Udrea A; Department of Automatic Control and Systems Engineering, University Politehnica of Bucharest, Bucharest, Romania.
Mitra GD; SkinVision BV, Amsterdam, The Netherlands.
Costea D; SkinVision BV, Amsterdam, The Netherlands.
Noels EC; Department of Automatic Control and Systems Engineering, University Politehnica of Bucharest, Bucharest, Romania.
Wakkee M; SkinVision BV, Amsterdam, The Netherlands.
Siegel DM; Department of Dermatology, Erasmus Medical Center, Rotterdam, The Netherlands.
de Carvalho TM; Department of Dermatology, Erasmus Medical Center, Rotterdam, The Netherlands.
Nijsten TEC; State University of New York Downstate Medical Center, Brooklyn, NY, USA.

J Eur Acad Dermatol Venereol ; 34(3): 648-655, 2020 Mar.

Article in En | MEDLINE | ID: mdl-31494983

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin Neoplasms / Mobile Applications / Machine Learning / Smartphone / Melanoma Type of study: Diagnostic_studies / Etiology_studies / Risk_factors_studies Limits: Humans Language: En Journal: J Eur Acad Dermatol Venereol Journal subject: DERMATOLOGIA / DOENCAS SEXUALMENTE TRANSMISSIVEIS Year: 2020 Document type: Article Affiliation country: Rumanía Country of publication: Reino Unido

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