Cataract, as an extremely common visual impairment disease, seriously affects the normal work and life of patients, and the optimization of cataract IOL model is of extraordinary significance to the diagnosis and treatment effect. The article collects ocular biological measurements of cataract surgery patients as experimental data, explores the radial basis function (RBF) neural network belonging to the field of artificial intelligence in the process of IOL calculation, and then introduces genetic algorithms to optimize the RBF neural network, and constructs the cataract IOL calculation model based on GA-RBF. The experimental results show that after combining the improved cataract IOL calculation model for telemedicine, the patient’s hospitalization days were shortened by 3.06 d, and the hospitalization cost decreased by $1,383.7, meanwhile, the patient’s satisfaction increased by 4.69%.