Evaluation of Changes in Facial Attractiveness and Estimated Facial Age After Blepharoplasty with an Artificial Intelligence Algorithm

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Blepharoplasty, Artificial intelligence, Facial age, Facial attractiveness


Objective: The aim of this study is to evaluate the effects of blepharoplasty operation on facial attractiveness and estimated facial age with an artificial intelligence-based algorithm over pre- and post-treatment facial photographs. In addition, it is aimed to make a comparison by reviewing the observable changes according to gender and operation type (upper, lower, combined).

Methods: Preoperative and postoperative photos of patients who underwent open access and copyright-free blepharoplasty operation on social media platforms (instagram and youtube) were collected. The photos were evaluated by an artificial intelligence algorithm trained to estimate facial age and evaluate facial attractiveness.

Results: A total of 541 patients, of which 454 (83.92%) were female and 87 (16.08%) were male. When all patients were evaluated without subgrouping, there was a -1.91±3.35 years younger face age and 0.43±0.64 point increase in facial attractiveness (p<0.005).

Conclusion: In this study, the effects of blepharoplasty on facial attractiveness and apparent age are presented with quantitative data. In addition, it has been concluded that artificial intelligence can be used in scoring the apparent age and facial attractiveness after blepharoplasty.


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How to Cite

Balel, Y. (2023). Evaluation of Changes in Facial Attractiveness and Estimated Facial Age After Blepharoplasty with an Artificial Intelligence Algorithm. European Journal of Therapeutics, 404–411. https://doi.org/10.58600/eurjther1648



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