| Summary: | Abstract
BackgroundAesthetic facial surgeries historically rely on subjective analysis in determining success; this limits objective comparison of surgical outcomes.
ObjectivesThis case study exemplifies the use of an artificial intelligence software on objectively analyzing facial rejuvenation techniques with the aim of reducing subjective bias.
MethodsRetrospectively, all patients who underwent facial rejuvenation surgery with concomitant procedures from 2015 to 2017 were included (nnnn
ResultsPostoperatively, Group A experienced a decrease in happiness by 0.84% and a decrease in anger by 6.87% (PPPP
ConclusionsThis study provides the first proof of concept for the use of a machine learning software application to objectively assess various aesthetic surgical outcomes in facial rejuvenation. Due to limitations in patient heterogeneity, this study does not claim one technique's superiority but serves as a conceptual foundation for future investigation.
Level of Evidence: 4
|
|---|