Artificial intelligence and ophthalmic surgery

Abstract

Purpose of review: Artificial intelligence and deep learning have become important tools in extracting data from ophthalmic surgery to evaluate, teach, and aid the surgeon in all phases of surgical management. The purpose of this review is to highlight the ever-increasing intersection of computer vision, machine learning, and ophthalmic microsurgery.

Recent findings: Deep learning algorithms are being applied to help evaluate and teach surgical trainees. Artificial intelligence tools are improving real-time surgical instrument tracking, phase segmentation, as well as enhancing the safety of robotic-assisted vitreoretinal surgery.

Summary: Similar to strides appreciated in ophthalmic medical disease, artificial intelligence will continue to become an important part of surgical management of ocular conditions. Machine learning applications will help push the boundaries of what surgeons can accomplish to improve patient outcomes.