Grading facial aging: Comparing the clinical assessments made by three dermatologists with those obtained by an AI-based scoring system that analyses selfie pictures. A focus on Chinese subjects of both genders.

Abstract

Objective: The objective of this study is to assess the correspondence, in live conditions, between clinical gradings of facial aging signs by three dermatologists and those afforded by an automatic AI-based algorithm that analyses smartphones' selfie images of Chinese subjects.

Methods: In total, 125 Chinese subjects of both genders, aged 18-62y, took a selfie using their own smartphones and were immediately viewed by three dermatologists. The latter graded the severity of 15 facial signs in women and 9 in men, using the standardized values afforded by a Skin Aging Atlas referential dedicated to Asian skin. The data issued by both methodologies were then statistically compared.

Results: The absolute gradings of the automatic system were found highly correlated with clinical assessments, with lower values in most cases. In women, large differences in absolute values were found on the gradings for size of isolated spot, cheek fold, spread macules, and texture of mouth contour women. Analysis of the Mean Absolute Errors (M.A.E) revealed that these rarely exceed 0.6 grading units in women and to a lesser extent in men.

Conclusion: The present study confirmed the value of the automatic system towards an extended use towards large human cohorts as a surrogate of clinical evaluations and allowed to detect the points where improvements must be brought to the system.