Optimizing Refractive Outcomes of SMILE: Artificial Intelligence versus Conventional State-of-the-Art Nomograms.
Nikolaus LuftNiklas MohrElmar SpiegelHannah MarchiJakob SiedleckiLisa HarrantWolfgang J MayerMartin DirisamerSiegfried G PriglingerPublished in: Current eye research (2023)
Machine learning endorsed the validity of state-of-the-art linear and non-linear SMILE nomograms. However, improving the accuracy of subjective manifest refraction seems warranted for optimizing ±0.50 D SE predictability beyond an apparent methodological 90% limit.