L'Oréal Research and Innovation, Clichy, France.
Department of Dermatology, Konkuk University School of Medicine, Seoul, Korea.
Skin Res Technol. 2021 Mar;27(2):183-190. doi: 10.1111/srt.12922. Epub 2020 Jul 20.
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.
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.
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.
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.
评估自动检测系统从智能手机自拍图像中准确分级新增的七种面部新标志严重程度的能力，这些标志已添加到之前整合的九种标志中。
采用两步法进行：首先，检查 112 名韩国女性，基于人工智能的自动分级系统如何与作为参考的皮肤科评估相关联；其次，在三个种族（非洲、亚洲和高加索）的 1140 名女性中确认新输入的面部标志的相关性。
自动检测到的 16 个特定的亚洲面部标志与两名韩国皮肤科医生的临床评估显著相关（皱纹：r=0.90；下垂：r=0.75-0.95；血管：r=0.85；毛孔：r=0.60；色素沉着：r=0.50-0.80）（P<0.0001）。当在不同种族的女性中大规模应用时，新标志被发现具有良好的准确性和可重复性，尽管取决于种族。由于与固有肤色的对比度，处理皮肤色素沉着的面部标志在亚洲女性中比非洲或高加索女性的相关性更高。自动分级甚至比临床分级具有更高的准确性。
以前使用的自动分级系统现在通过添加新的面部标志得到了补充，这些标志适合被检测到。现在的持续发展正在整合一些与自拍对象固有肤色有关的限制。本系统提供了一种易于、快速、经济实惠且保密的方法，对面部标志进行客观量化，从而对临床研究产生巨大影响，如在流行病学研究中，它提供了一种易于、快速、经济实惠且保密的方法，对面部标志进行客观量化。
