Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.

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Title: Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.
Authors: Tschandl P; ViDIR Group, Department of Dermatology, Medical University of Vienna, Vienna, Austria., Codella N; IBM Research AI, T J Watson Research Center, Yorktown Heights, NY, USA., Akay BN; Department of Dermatology, Medicine Faculty, Ankara University, Ankara, Turkey., Argenziano G; Dermatology Unit, University of Campania, Naples, Italy., Braun RP; Skin Cancer Center, Department of Dermatology, University Hospital Zürich, Zürich, Switzerland., Cabo H; Department of Dermatology, Instituto de Investigaciones Médicas, Buenos Aires, Argentina., Gutman D; Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA., Halpern A; Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Helba B; Kitware, Clifton Park, NY, USA., Hofmann-Wellenhof R; Department of Dermatology, Medical University Graz, Graz, Austria., Lallas A; First Department of Dermatology, Aristotle University, Thessaloniki, Greece., Lapins J; Department of Dermatology, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden., Longo C; Department of Dermatology, University of Modena and Reggio Emilia, Modena, Italy; Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Centro Oncologico ad Alta Tecnologia Diagnostica-Dermatologia, Reggio Emilia, Italy., Malvehy J; Melanoma Unit, Dermatology Department, Hospital Clínic Barcelona, Universitat de Barcelona, IDIBAPS, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Rarasd (CIBER ER), Instituto de Salud Carlos III, Barcelona, Spain., Marchetti MA; Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Marghoob A; Memorial Sloan Kettering Cancer Center, Hauppauge, NY, USA., Menzies S; Sydney Melanoma Diagnostic Centre & Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia., Oakley A; Department of Dermatology, Waikato District Health Board and Waikato Clinical Campus, University of Auckland, Hamilton, New Zealand., Paoli J; Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden., Puig S; Melanoma Unit, Dermatology Department, Hospital Clínic Barcelona, Universitat de Barcelona, IDIBAPS, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Rarasd (CIBER ER), Instituto de Salud Carlos III, Barcelona, Spain., Rinner C; Center for Medical Statistics, Informatics and Intelligent Systems (CeMSIIS), Medical University of Vienna, Vienna, Austria., Rosendahl C; School of Clinical Medicine, University of Queensland, University of Queensland, Brisbane, QLD, Australia., Scope A; Medical Screening Institute, Sheba Medical Center and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel., Sinz C; ViDIR Group, Department of Dermatology, Medical University of Vienna, Vienna, Austria., Soyer HP; Dermatology Research Centre, The University of Queensland Diamantina Institute, University of Queensland, Brisbane, QLD, Australia., Thomas L; Department of Dermatology, Hospitalier Lyon Sud, Lyon, France; Lyon Cancer Research Center INSERM U1052-CNRS UMR5286, Lyon, France; Lyon 1 University, Lyon, France., Zalaudek I; Dermatology Clinic, Maggiore Hospital, University of Trieste, Trieste, Italy., Kittler H; ViDIR Group, Department of Dermatology, Medical University of Vienna, Vienna, Austria. Electronic address: harald.kittler@meduniwien.ac.at.
Source: The Lancet. Oncology [Lancet Oncol] 2019 Jul; Vol. 20 (7), pp. 938-947. Date of Electronic Publication: 2019 Jun 12.
Publication Type: Comparative Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Lancet Pub. Group Country of Publication: England NLM ID: 100957246 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1474-5488 (Electronic) Linking ISSN: 14702045 NLM ISO Abbreviation: Lancet Oncol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1474-5488
DOI:10.1016/S1470-2045(19)30333-X