Design of Postoperative Visual Acuity Prediction Program Based on Machine Learning before Cataract Surgery

With the rapid development of modern artificial intelligence technology, its practice and application in different fields has gradually developed, and the medical field is no exception. The application of artificial intelligence technology based on machine learning in ophthalmology is one of them. The eye image is fine, complex, and informative. The diagnosis results are often limited by the doctor's knowledge level and clinical experience, subjective, time-consuming and labor-intensive. The application of artificial intelligence technology of machine learning combined with computer in ophthalmology can greatly improve the diagnostic efficiency of ophthalmic diseases in clinical work and reduce the burden on ophthalmologists. This article aims to analyze the predictive value of postoperative visual acuity before cataract surgery based on the indicators of preoperative examination of cataract patients and the patient's living habits and disease cognition levels.