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TitelA new nomogram for laser corneal refractive surgery based on Artificial intelligence
DoelTo predict delta between programmed laser treatment and really delivered treatment.
To compare the predicted delta with the wavelight nomogram
To study relative importance of each preoperative parameter.
MethodesWe reviewed 2728 myopic eyes operated with Wavelight Refractive Suite. Preoperative and one-month postoperative refractions and programmed treatment defined the observed delta. Delta is then predicted from clinical, laser and topographical preoperative parameters using machine learning regression algorithm.
ResultatenMachine learning nomogram reduced the error and improve outcomes. Outcomes are also improved after using machine learning and Wavelight nomogram.
Programmed spherical equivalent is the more influential parameter to predict sphere and programmed astigmatism is the more influential parameter to predict cylinder.
ConclusieMachine learning could allow to increase laser treatment accuracy and our understanding of causes of residual errors.
BelangenverstrengelingNee
Auteur 1
NaamCRAHAY
InitialenF-X
InstituutCHR Citadelle
StadLiège
Auteur 2
NaamDebellemaniere
InitialenG
InstituutFondation Ophtalmologique Adolphe de Rothschild
StadParis
Auteur 3
NaamRampat
InitialenR
InstituutFondation Ophtalmologique Adolphe de Rothschild
StadParis
Auteur 4
NaamMoran
InitialenS
InstituutFondation Ophtalmologique Adolphe de Rothschild
StadParis
Auteur 5
NaamGatinel
InitialenD
InstituutFondation Ophtalmologique Adolphe de Rothschild
StadParis
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