Artificial intelligence, anterior segment and refractive surgery: Which relationship and association?

Aims/Purpose: The goal of our work is to synthesize the different fields identified by AI in refractive surgery. Methods: Research in the literature of the different manifestations of artificial intelligence related to refractive surgery. Results: 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 sensitivity of 85.2% and specificity 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 algorithm 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. Conclusions: 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. References 1. Artificial intelligence in ophthalmology ‐ Machines think! Indian J Ophthalmol avr 2022. 2. Artificial intelligence in ophthalmology: A multidisciplinary approach. 2022. 3. Artificial Intelligence for Anterior Segment Diseases: A Review of Potential Developments and Clinical Applications mai 2023.