The Role of Artificial Intelligence With Deep Convolutional Neural Network in Screening Melanoma: A Systematic Review and Meta-Analyses of Quasi-Experimental Diagnostic Studies.

Journal: The Journal of craniofacial surgery
Published Date:

Abstract

INTRODUCTION: Detecting melanoma as one of the most common skin cancer with using artificial intelligence (AI), such as deep convolutional neural network (DCNN) have the potency to increase the accuracy of the diagnosis. The aim of this study is to analyze the sensitivity, specificity, precision, and F1-score of DCNN in screening melanoma.

Authors

  • Stella Maureen Miracle
    School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia.
  • Louis Rianto
    Faculty of Medicine, Tarumanagara University, Jakarta.
  • Kelvin Kelvin
    Faculty of Medicine, Tarumanagara University, Jakarta.
  • Kevin Tandarto
    School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia.
  • Felix Setiadi
    School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia.
  • Angela Angela
    Faculty of Medicine, Kristen Duta Wacana University, Yogyakarta.
  • Thiara Maharani Brunner
    Faculty of Medicine, Universitas Indonesia.
  • Hari Darmawan
    Department of Dermatovenereology, Faculty of Medicine, Tarumanagara University, Jakarta.
  • Henry Tanojo
    Melania Clinic, Surabaya, Indonesia.
  • Rosalyn Kupwiwat
    Chulabhorn International College of Medicine, Thammasat University, Bangkok.
  • Inneke Jane Hidajat
    Department of Dermatology and Venereology, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia.
  • Rungsima Wanitphakdeedecha
    Department of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
  • Kyu-Ho Yi
    Division in Anatomy and Developmental Biology, Department of Oral Biology, Human Identification Research Institute, BK21 FOUR Project, Yonsei University College of Dentistry, Seoul, Korea.

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