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

Seungbin ParkHannah KimLaehyun KimJin-Kuk KimIn Sik LeeIk Hee RyuYoungjun Kim
Published in: Biomedical engineering online (2021)
Among the diverse machine learning algorithms, AdaBoost exhibited the highest performance in the prediction of the sphere, cylinder, and astigmatism axis nomograms for SMILE. The study proved the feasibility of applying artificial intelligence (AI) to nomograms for SMILE. Also, it may enhance the quality of the surgical result of SMILE by providing assistance in nomograms and preventing the misdiagnosis in nomograms.
Keyphrases
  • artificial intelligence
  • machine learning
  • big data
  • deep learning
  • lymph node metastasis
  • quality improvement
  • squamous cell carcinoma
  • cataract surgery