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Corneal biomechanics in early diagnosis of keratoconus using artificial intelligence.

Yan HuoXuan ChenGauhar Ali KhanYan Wang
Published in: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie (2023)
Keratoconus is a blinding eye disease that affects activities of daily living; therefore, early diagnosis is crucial. Great efforts have been made toward an early diagnosis of keratoconus. Recent studies have shown that corneal biomechanics is associated with the occurrence and progression of keratoconus. Hence, detecting changes in corneal biomechanics may provide a novel strategy for early diagnosis. However, an early keratoconus diagnosis remains challenging due to the subtle and localized nature of its lesions. Artificial intelligence has been used to help address this problem. Herein, we reviewed the literature regarding three aspects of keratoconus (keratoconus, early keratoconus, and keratoconus grading) based on corneal biomechanical properties using artificial intelligence. Furthermore, we summarized the current research progress, limitations, and possible prospects.
Keyphrases
  • artificial intelligence
  • machine learning
  • big data
  • deep learning
  • optical coherence tomography
  • wound healing
  • risk assessment
  • cataract surgery
  • finite element analysis