Artificial Intelligence in Surgical Evaluation: A Study of Facial Rejuvenation Techniques

Personalized Research on the Aging Face-A Narrative History

Throughout history, people have struggled to find out the secret of youth. The aim of the manuscript is to review the main achievements regarding the exploration of the aging face phenomenon. It should be very important to know the evolution in this field due to the increase in life expectancy among the population. Our purpose is for the current study to serve as a starting point towards exploring novel research avenues in molecular biology and the confocal immunofluorescence of cervicofacial soft tissues, employing cutting-edge techniques. All changes in the shape of the facial skeleton, soft tissue, retaining ligaments, fat compartments, and the skin envelope contribute to facial aging to varying degrees.

Artificial Intelligence Versus Human Focus Group Rating of Facial Attractiveness

Background: Many open-access artificial intelligence (AI)-based websites that rate facial attractiveness are available, but none have been compared with human focus group outcomes. Objective: To compare human and AI-based websites scoring of facial attractiveness of adult female white faces. Methods: A 40-photograph database of AI-generated adult, white, female, expressionless, and frontal-view facial images were scored by otolaryngology residents and five AI-based facial rating websites: prettyscale.com, attractivenesstest.com, face-score.com/en, hotchat3000.com, and beautyscoretest.com. Sample t-test and bivariate correlation were performed for statistical analyses. Results: The focus group of 24 otolaryngology residents consisted of 62.5% males and 58.3% white participants. There was a strong positive correlation between average human score and average AI score for each photo (Pearson's correlation 0.84, p < 0.01). The average human raters' scores were significantly lower than the average AI scores (5.0 ± 1.8 vs. 6.9 ± 0.9, p < 0.01). Thirty images (75.0%) had statistically higher scores from the AI websites versus the focus group. On correlation analysis, all AI-based websites individually had scores that positively correlate with the human scores (all p < 0.05). Conclusion: AI-based websites and human focus-group scoring of facial attractiveness of adult white female faces were significantly correlated with the AI ratings biased toward higher values, encouraging their cautious utilization in future research.

Using Artificial Intelligence to Quantify Sexual Dimorphism in Aesthetic Faces: Analysis of 100 Facial Points in 42 Caucasian Celebrities

Background

Sexual dimorphism has been studied in the faces of average populations and worldwide celebrities; however, a focused analysis of attractive Caucasian faces has not been conducted.

Objective

The study harnesses the power of artificial intelligence (AI) to efficiently analyze these facial patterns in attractive Caucasian male and female celebrities.

Methods

Twenty-one male and 21 female Caucasian celebrities were selected based on popular editorial rankings, modeling agencies, and casting directors from 2017 to 2022. Frontal photographs of celebrities aged 23 to 42 without facial animation were selected. One hundred facial landmarks were identified using semi-automatic image analysis software consisting of modified Apple Vision (Cupertino, CA) machine-learning algorithms with additional custom landmarks. Measurements were converted to absolute distances by fixing subjects' white-to-white corneal diameters to the validated average in Caucasians.

Results

Attractive females had significantly greater upper and middle facial proportions, more uniformly divided facial thirds, and greater canthal tilt compared with males. Attractive males had significantly greater facial height, bizygomatic and bigonial widths, medial and total brow lengths, and alar width than females. The golden ratio (1.618) was observed in the ratio of facial height to bigonial width in females (1.613), and attractive males closely approximated that ratio (1.566). There were no significant differences in interpupillary distances, eyebrow angles, or horizontal palpebral fissure lengths. No faces in either sex exhibited scleral show.

Conclusions

The study is the first to utilize AI in quantifying key sexual dimorphisms among Caucasian celebrity faces. Identifying these contemporary patterns may provide valuable considerations in planning facial aesthetic and gender affirmation surgery.

Level of Evidence 3