Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network

• Seung Seog Han ,

  Contributed equally to this work with: Seung Seog Han, Gyeong Hun Park

  Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliation I Dermatology, Seoul, Korea

  http://orcid.org/0000-0002-0500-3628

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• Gyeong Hun Park ,

  Contributed equally to this work with: Seung Seog Han, Gyeong Hun Park

  Roles Investigation, Methodology, Resources, Validation

  Affiliation Department of Dermatology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Dongtan, Korea

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• Woohyung Lim,

  Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Validation, Visualization, Writing – original draft

  Affiliation SK Telecom, HMI Tech. Lab, Seoul, Korea

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• Myoung Shin Kim,

  Roles Investigation, Methodology, Resources, Validation

  Affiliation Department of Dermatology, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea

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• Jung Im Na,

  Roles Resources, Validation

  Affiliation Department of Dermatology, Seoul National University College of Medicine, Seoul, Korea

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• Ilwoo Park,

  Roles Methodology, Software, Validation, Visualization, Writing – review & editing

  Affiliation Department of Radiology, Chonnam National University Medical School and Hospital, Gwangju, Korea

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• Sung Eun Chang

  Roles Project administration, Supervision

  * E-mail: csesnumd@gmail.com

  Affiliation Department of Dermatology, Asan Medical Center, Ulsan University College of Medicine, Seoul, Korea

  http://orcid.org/0000-0003-4225-0414

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