Frederic Flament1, Yang Won Lee2, Dong Hun Lee3, Thierry Passeron4,5, Yuze Zhang6, Ruowei Jiang6, Anne Prunel7,8, Seema Dwivedi9, Camille Kroely9, Youn Jung Park10, Bertrand Chuberre11, Parham Aarabi6. 1. L'Oréal Research and Innovation, Clichy, France. 2. Department of Dermatology, Konkuk University School of Medicine, Seoul, Korea. 3. Department of Dermatology, Seoul National University College of Medicine, Seoul, Korea. 4. Department of Dermatology, CHU Nice, University Côte d'Azur, Nice, France. 5. INSERM U1065, C3M, University Côte d'Azur, Nice, France. 6. ModiFace - A L'Oréal Group Company, Toronto, ON, Canada. 7. L'Oréal Research and Innovation, Tokyo, Japan. 8. L'Oréal Korean Innovation Center, Seoul, Korea. 9. L'Oréal CDO - Digital Service Factory, Clichy, France. 10. Active Cosmetics International, Korean Medical Relations, Seoul, Korea. 11. Active Cosmetics International, Global Medical Relations and Communications, Levallois, France.
Abstract
OBJECTIVE: To evaluate the capacity of the automatic detection system to accurately grade, from smartphones' selfie pictures, the severity of seven new facial signs added to the nine previously integrated. METHODS: A two-step approach was conducted: first, to check on 112 Korean women, how the AI-based automatic grading system may correlate with dermatological assessments, taken as reference; second, to confirm on 1140 women of three ancestries (African, Asian, and Caucasian) the relevance of the newly input facial signs. RESULTS: The sixteen specific Asian facial signs, detected automatically, were found significantly (P < .0001) highly correlated with the clinical evaluations made by two Korean dermatologists (wrinkles: r = .90; sagging: r = .75-.95; vascular: r = .85; pores: r = .60; pigmentation: r = .50-.80). When applied at a larger scale on women of different ethnicities, new signs were found of good accuracy and reproducibility, albeit depending on ethnicity. Due to contrast with the innate skin complexion, the facial signs dealing with skin pigmentation were found of a much higher relevance among Asian women than African or Caucasian women. The automatic gradings were even found of a slightly higher accuracy than the clinical gradings. CONCLUSION: The previously used automatic grading system is now completed by adding new facial signs apt at being detected. The continuous development is now integrating some limitations with regard to the constitutive skin complexion of the self-pictured subjects. Presenting reproducible assessments, highly correlated with medical grading, this system could change tremendously clinical researches, like in epidemiological studies, where it offers an easy, fast, affordable, and confidential approach in the objective quantification of facial signs.
OBJECTIVE: To evaluate the capacity of the automatic detection system to accurately grade, from smartphones' selfie pictures, the severity of seven new facial signs added to the nine previously integrated. METHODS: A two-step approach was conducted: first, to check on 112 Korean women, how the AI-based automatic grading system may correlate with dermatological assessments, taken as reference; second, to confirm on 1140 women of three ancestries (African, Asian, and Caucasian) the relevance of the newly input facial signs. RESULTS: The sixteen specific Asian facial signs, detected automatically, were found significantly (P < .0001) highly correlated with the clinical evaluations made by two Korean dermatologists (wrinkles: r = .90; sagging: r = .75-.95; vascular: r = .85; pores: r = .60; pigmentation: r = .50-.80). When applied at a larger scale on women of different ethnicities, new signs were found of good accuracy and reproducibility, albeit depending on ethnicity. Due to contrast with the innate skin complexion, the facial signs dealing with skin pigmentation were found of a much higher relevance among Asian women than African or Caucasian women. The automatic gradings were even found of a slightly higher accuracy than the clinical gradings. CONCLUSION: The previously used automatic grading system is now completed by adding new facial signs apt at being detected. The continuous development is now integrating some limitations with regard to the constitutive skin complexion of the self-pictured subjects. Presenting reproducible assessments, highly correlated with medical grading, this system could change tremendously clinical researches, like in epidemiological studies, where it offers an easy, fast, affordable, and confidential approach in the objective quantification of facial signs.