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Background:

Male-to-female transgender patients desire to be identified, and treated, as female, in public and social settings. Facial feminization surgery entails a combination of highly visible changes in facial features. To study the effectiveness of facial feminization surgery, we investigated preoperative/postoperative gender-typing using facial recognition neural networks.

Methods:

In this study, standardized frontal and lateral view preoperative and postoperative images of 20 male-to-female patients who completed hard-and soft-tissue facial feminization surgery procedures were used, along with control images of unoperated cisgender men and women (n= 120 images). Four public neural networks trained to identify gender based on facial features analyzed the images. Correct gender-typing, improvement in gender-typing (preoperatively to postoperatively), and confidence in femininity were analyzed.

Results …