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Past and present of computer-assisted dermoscopic diagnosis: performance of a conventional image analyser versus a convolutional neural network in a prospective data set of 1,981 skin lesions.
Sies, Katharina; Winkler, Julia K; Fink, Christine; Bardehle, Felicitas; Toberer, Ferdinand; Buhl, Timo; Enk, Alexander; Blum, Andreas; Rosenberger, Albert; Haenssle, Holger A.
Affiliation
  • Sies K; Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Winkler JK; Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Fink C; Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Bardehle F; Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Toberer F; Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Buhl T; Department of Dermatology, University of Göttingen, Göttingen, Germany.
  • Enk A; Department of Dermatology, University of Heidelberg, Heidelberg, Germany.
  • Blum A; Office Based Clinic of Dermatology, Konstanz, Germany.
  • Rosenberger A; Department of Genetic Epidemiology, University of Goettingen, Goettingen, Germany.
  • Haenssle HA; Department of Dermatology, University of Heidelberg, Heidelberg, Germany. Electronic address: holger.haenssle@med.uni-heidelberg.de.
Eur J Cancer ; 135: 39-46, 2020 08.
Article in En | MEDLINE | ID: mdl-32534243
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin Neoplasms / Image Interpretation, Computer-Assisted / Diagnosis, Computer-Assisted / Dermoscopy / Deep Learning / Melanoma Type of study: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Eur J Cancer Year: 2020 Document type: Article Affiliation country: Germany Country of publication: United kingdom
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin Neoplasms / Image Interpretation, Computer-Assisted / Diagnosis, Computer-Assisted / Dermoscopy / Deep Learning / Melanoma Type of study: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Eur J Cancer Year: 2020 Document type: Article Affiliation country: Germany Country of publication: United kingdom