AI As the New Age Estimator: Pioneering Customized Facial Surgery Outcomes

• DOI: 10.1093/asjof/ojae007.087
• Publication Date: 2024-04-12T16:55:54Z
• Authors: Khaled Alameddine; Jess Rames; Karim Bakri; Samir Mardini
• Keywords: Feature (linguistics); Margin (machine learning); Softmax function; Rhytidectomy

Abstract Goals/Purpose The imperative for precision in aesthetic surgery necessitates a robust framework evaluating the impact of facial interventions on perceived age. Our study introduces cutting-edge AI model aimed at discerning an individual's age from characteristics. This tool is designed to augment assessment various plastic procedures, facilitating tailoring each patient's unique aging pattern. Methods/Technique We harnessed deep convolutional neural network (DCNN), pre-trained extensive ImageNet dataset, and further refined using 523,051 pre-annotated images IMBD-WIKI database, normalized as per Mathias et al. face detection paradigm. Faces were processed into 299x299 pixel matrix, maintaining 40% margin around uniformity. Xception architecture was employed its advanced feature extraction capabilities. tested against diverse set 100 patient faces Mayo Clinic's categorized by demographic procedural data. regression analysis softmax probability precise estimation. Results/Complications exhibited remarkable accuracy rate 92.5% estimation pre patients, with standard deviation 3.2 years. It significantly outperformed traditional methods identifying fine-grained age-related features. discerned average reduction 3.5 years across all patients post-procedure, notable variance among different types surgeries. Certain such rhytidectomy blepharoplasty, showed more pronounced age-reduction effect. Conclusion presents accurate objective method quantifying age, serving significant benchmark evaluation. By illustrating measurable following some surgeries yielding substantial changes stands testament effectiveness interventions. our predicting pre- post-procedure underscores potential assist surgeons custom-tailoring individual patterns. innovation poised refine decision-making process surgery, ensuring treatments are aligned desired outcomes rejuvenation patient-specific needs, ultimately advancing frontier personalized surgery.