Eyeworld

I ARTIFICIAL INTELLIGENCE N FOCUS 38 | EYEWORLD | AUGUST 2020 Contact Ambrósio: dr.renatoAmbrósio@gmail.com Wallace: dw@la-sight.com laser (SMILE) has certain limitations. Second, identification of certain corneal anatomy by machine, such as the visual axis, angle kappa, and other features, is to some extent variable from machine to machine, so there may not be enough consistency to agree on the input data to guide output for treatment planning. Third, I honestly think that we are going to have several years of adaptation to AI in a strictly diagnostic mode, and that is going to need to precede any thinking about artificial intelligence in a treat- ment capacity," he said. Ultimately, Dr. Wallace cautioned against machines being "as good or better than a skilled, experienced refractive surgeon." "… most of us who are experienced laser refractive surgeons have spent years or decades getting here, and I don't think it's going to be "There are a lot of factors that go into do- ing this right that are an important part of the process. There is no guarantee that every system that uses big data is going to generate inspired and thoughtful clinical-assisted diagnostics or analytics. It's the combination of the big data capability, the thoughtful approach, and the selective use of good data that allows advances in this space," Dr. Wallace said. Considering crosslinking There are two main possibilities for AI in planning crosslinking, Dr. Ambrósio said. The finite element modeling from William Dupps, MD, PhD, has been used to create customized crosslinking algorithms, he said, and the use of AI for prognostic factors is also promising. "In my routine, I consider the current pa- rameters as the stiffness parameter described by Cynthia Roberts, PhD. But longitudinal studies are underway to develop such AI prognostic factors," Dr. Ambrósio said. As new parameters are added to datasets, such as biomechanics, Dr. Ambrósio said he thinks the ability to detect and characterize disease will be improved. Dr. Wallace weighed in on the utility of artificial intelligence in crosslinking planning, first noting its potential to identify topographic asymmetry and early keratoconus for referrals for crosslinking. Second, will topography be able to guide custom treatment including com- bined excimer and CXL? he asked. "In theory certainly, but the devil is in the details. The details require much more informa- tion than just corneal topography from anterior surface Placido reflectance as an input dataset. You would want to know thickness mapping, you might want to know something about corneal biomechanics; that is not assumed just from thickness mapping," Dr. Wallace said. Predicting refractive surgery outcomes Dr. Ambrósio said beyond screening for ectasia risk, AI is promising for augmenting efficiency and predictability of refractive surgery. Dr. Wallace was guarded in his opinion for AI's utility in refractive surgery. "First, laser treatment technology with either excimer (PRK, LASIK) or femtosecond continued from page 37 References 1. Lopes BT, et al. Artificial intelligence in corneal diagnosis: Where are we? Curr Ophthalmol Rep. 2019;7:204–211. 2. Esporcatte LPG, et al. Bio- mechanical diagnostics of the cornea. Eye Vis (Lond). 2020;7:9. 3. Ambrosio JR, et al. Assess- ing ectasia susceptibility prior to LASIK: the role of age and residual stromal bed (RSB) in conjunction to Belin-Ambrósio deviation index (BAD-D). Rev Bras Oftalmol. 2014;73:75–80. Relevant disclosures Ambrósio: Oculus, Alcon, Carl Zeiss Meditec, Allergan, Mediphacos Wallace: Intelligent Diagnostics A few AI papers at the 2020 ASCRS Virtual Annual Meeting •"Diagnostic Performance of an Arti- ficial Intelligence Algorithm in Fuchs Endothelial Cell Dystrophy" found AI to be a viable option for Fuchs detection with "excellent accuracy, sensitivity, and specificity," though prospective studies are still required to evaluate AI's utility in assessing Fuchs progression. •"A Prospective Study for Autonomous Diagnosis of Dry Eye Syndrome Using an Artificial Intelligence Algorithm" found that the algorithm used with an- terior segment OCT could be helpful in diagnosing dry eye disease. •"An Artificial Intelligence (AI) Algo- rithm for the Autonomous Diagnosis of Corneal Graft Rejection" determined that AI can accurately diagnose graft rejections.

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