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

BACKGROUND: Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human experts is unclear. The aim of this study was to compare the diagnostic accuracy of state-of-the-art machine-learning algorithms with human readers for all clinically relevant types of beni...

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Gepubliceerd in:Lancet Oncol
Hoofdauteurs: Tschandl, Philipp, Codella, Noel, Akay, Bengü Nisa, Argenziano, Giuseppe, Braun, Ralph P, Cabo, Horacio, Gutman, David, Halpern, Allan, Helba, Brian, Hofmann-Wellenhof, Rainer, Lallas, Aimilios, Lapins, Jan, Longo, Caterina, Malvehy, Josep, Marchetti, Michael A, Marghoob, Ashfaq, Menzies, Scott, Oakley, Amanda, Paoli, John, Puig, Susana, Rinner, Christoph, Rosendahl, Cliff, Scope, Alon, Sinz, Christoph, Soyer, H Peter, Thomas, Luc, Zalaudek, Iris, Kittler, Harald
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: 2019
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Article
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC8237239/
https://ncbi.nlm.nih.gov/pubmed/31201137
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/S1470-2045(19)30333-X
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