OBJECTIVE: To apply artificial intelligence (AI) for automated identification of corneal condition and prediction of the likelihood of need for future keratoplasty intervention from optical coherence tomography (OCT)-based corneal parameters.
PURPOSE: To predict 10-year graft survival after deep anterior lamellar keratoplasty (DALK) and penetrating keratoplasty (PK) using a machine learning (ML)-based interpretable risk score.
Machine learning can be used to identify risk factors associated with graft rejection after corneal transplantation for keratoconus. The study included all keratoconus eyes that underwent primary corneal transplantation from 1994 to 2021. Data relati...