AI-powered Glaucoma Management: Predicting the Optimal Surgical Treatment

Introduction: Glaucoma is the leading cause of irreversible blindness worldwide, and due to changing demographics leading to increased prevalence, pressure on ophthalmic services is growing rapidly in many countries. Recently there has been a rapid increase in new surgical techniques to prevent sight loss from glaucoma with the introduction of Minimally Invasive Glaucoma Surgery (MIGS). This is a relatively new set of techniques with increasing evidence regarding efficacy however it is not yet clear which glaucoma surgery is the optimum procedure to perform in different clinical scenarios. Methods: We developed an Adaptive Neuro Fuzzy Inference System (ANFIS) AI model to help surgeons decide which surgical technique would likely have the best outcome for an individual patient depending on core clinical parameters such as vision and intraocular pressure. The model was also able to accurately predict clinical outcomes such as vision, intraocular pressure and number of medications at 1 year. Results: The ANFIS model had a very high degree of accuracy both in predicting clinical parameters such as vision and intraocular pressure 1 year after surgery and in determining the optimum surgery in different clinical scenarios. Discussion: With the increasing array of available MIGS procedures as well as traditional glaucoma surgery, AI could provide a powerful tool to help surgeons decide, in collaboration with their patients, on the optimum procedure. As the training data comes from an international registry, and so represents real world results across different surgeons and surgical centers, this makes it a powerful tool to help surgeons to practice evidence-based medicine whilst harnessing these new techniques to treat patients with glaucoma.