Artificial intelligence-based nomogram for small-incision lenticule extraction.

Journal: Biomedical engineering online
PMID:

Abstract

BACKGROUND: Small-incision lenticule extraction (SMILE) is a surgical procedure for the refractive correction of myopia and astigmatism, which has been reported as safe and effective. However, over- and under-correction still occur after SMILE. The necessity of nomograms is emphasized to achieve optimal refractive results. Ophthalmologists diagnose nomograms by analyzing the preoperative refractive data with their individual knowledge which they accumulate over years of experience. Our aim was to predict the nomograms of sphere, cylinder, and astigmatism axis for SMILE accurately by applying machine learning algorithm.

Authors

  • Seungbin Park
    Center for Bionics, Korea Institute of Science and Technology, Seoul, Korea.
  • Hannah Kim
    Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
  • Laehyun Kim
  • Jin-Kuk Kim
    B&VIIT Eye Center, Seoul, Korea.
  • In Sik Lee
    B&VIIt Eye Center, Seoul, South Korea.
  • Ik Hee Ryu
    B&VIIt Eye Center, Seoul, South Korea.
  • Youngjun Kim