Randomized clinical trial assessed perceived age reduction in facelift techniques, revealing no significant differences, and indicating AI assessments align well with humans.
Introduction: Perceived age is an objective surrogate for facial rejuvenation, but comparative evidence across facelift techniques using human and AI raters is limited.Objectives& Hypotheses: This trial assessed whether facelift techniques differ in rejuvenation effect and whether AI estimates align with human evaluations. Study Design: Randomized clinical trial. Methods: Thirty women (45-65 years) underwent rhytidectomy by Deep Plane, High SMAS, or Plication (n=10 each). Standardized photographs were rated by 200 laypersons (9,000 evaluations) and three AI models (180 evaluations). Primary outcome was change in perceived age (Δ age); secondary analyses included technique comparison, AI accuracy, rater bias, and human-AI correlation. Results: All techniques significantly reduced perceived age, with no statistical difference between groups. Amazon Rekognition and HowOldDoYouLook were more accurate.Human-AI correlation was moderate (r=0.41, p=0.020). Raters under 30 underestimated age (p<0.001). Conclusions: Human and AI evaluations showed no technique differences, with AI estimates resembling human assessments.
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Baptista et al. (2025) studied this question.
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