Accuracy and clinical relevance of an automated, algorithm-based analysis of facial signs from selfie images of women in the United States of various ages, ancestries and phototypes: A cross-sectional observational study.

Journal: Journal of the European Academy of Dermatology and Venereology : JEADV
Published Date: Sep 9, 2022

Abstract

BACKGROUND: Real-life validation is necessary to ensure our artificial intelligence (AI) skin diagnostic tool is inclusive across a diverse and representative US population of various ages, ancestries and skin phototypes.

Authors

  • Frederic Flament
    L'Oréal Research and Innovation, Clichy, France.
  • Ruowei Jiang
    ModiFace - A L'Oréal Group Company, Toronto, ON, Canada.
  • Jeff Houghton
    ModiFace - A L'Oréal Group Company, Toronto, ON, Canada.
  • Yuze Zhang
    ModiFace - A L'Oréal Group Company, Toronto, ON, Canada.
  • Camille Kroely
    L'Oréal CDO-Digital Service Factory, Clichy, France.
  • Nina G Jablonski
    Department of Anthropology, The Pennsylvania State University, University Park, State College, Pennsylvania, USA.
  • Aurélie Jean
    In Silico Veritas, 4 rue Joseph Granier, 75007 Paris, France.
  • Jeffrey Clarke
    Evaluative Criteria Incorporated, Tarrytown, New York, USA.
  • Jason Steeg
    Evaluative Criteria Incorporated, Tarrytown, New York, USA.
  • Cassidy Sehgal
    L'Oréal Research and Innovation, Clark, New Jersey, USA.
  • James McParland
    L'Oréal Research and Innovation, Clark, New Jersey, USA.
  • Caroline Delaunay
    L'Oréal Research and Innovation, Clichy, France.
  • Thierry Passeron
    Department of Dermatology, Université Côte d'Azur, CHU Nice, Nice, France.

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