ESCRS - P176 - ARTIFICIAL INTELLIGENCE AND REFRACTIVE SURGERY : WHICH ASSOCIATION ?

ARTIFICIAL INTELLIGENCE AND REFRACTIVE SURGERY : WHICH ASSOCIATION ?

Published 2023 - 27th ESCRS Winter Meeting

Reference: P176 | Type: Presented Poster & Poster Submission | DOI: 10.82333/kv3f-cj35

Authors: Sara Ettouri* 1 , Ghizlane Daghouj 2 , Manal Samie 1 , Reda Benchekroun 1 , Loubna EL Maaloum 1 , Bouchra Allali 1 , Asmaa El Kettani 1

1Department of pediatric ophthalmology,20 August Hospital . Pediatric Ophthalmology,Casablanca,Morocco, 2Department of pediatric ophthalmology ,20 August Hospital . Pediatric Ophthalmology,Casablanca,Morocco

Purpose

The purpose of our work is to synthesize the different fields identified by AI in refractive surgery.

Setting

Description 

Methods

Research in the literature of the different manifestations of artificial intelligence related to refractive surgery

Results

Several articles including reviews reporting the contribution of IA in refractive surgery:

With the increasing demand for optimal visual and refractive outcome and minimal risk of postoperative complications, there has been an increasing amount of AIrelated research in the field of refractive surgery, particularly preoperative screening for risk of ectasia after corneal laser refractive surgery, guiding the selection of the type of refractive surgery, and automated refraction. Identify candidates with high risk of iatrogenic ectasia is very important. Several articles including reviews reported several studies done in this direction. Lops and al introduced the PRFI (Pentacam Random Forest Index ) using data from 3 different countries . The PRFI has a sensivity of 85,2% and specifity of 96,6%. Xie and Co developed PIRSS (Pentacam InceptionResNetV2 Screening ) for refractive surgery with a little number of false positive in identifying normal cornea, suspected irregular and keratoconic cornea . AI has also been used in recommending the appropriate refractive surgery and nomograms used, Kamiya and al developed an ML-based algorithme to predict the postoperative posterior chamber phakic intraocular lens (IOL) vault using preoperative AS-OCT images of patients undergoing phakic IOL implantation to predict the achieved vault . These examples of studies and discoveries open new horizons in refractive surgery using AI

Conclusion

AI has been successfully used in the prediction of diagnosis of various corneal disorders, including IK, keratoconus, pterygium, endothelial diseases, and corneal graft-related complications but also in refractive surgery; certainly it has limits but next to telemedicine , 5G/6G networks, Quantum Communication Networks and Internet of Medical Things , AI is likely to form part of the new health care revolution .