Cataract Surgery

Cataract surgery research is intensely focused on improving both the surgical procedure and patient experience through technological advancements. Current efforts leverage deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers, to analyze surgical videos for automated phase recognition, instrument identification, and prediction of post-operative complications like intraocular lens dislocation. These advancements aim to enhance surgical precision, efficiency, and patient outcomes, while also improving access to information and reducing the burden on healthcare professionals through AI-powered chatbots and automated image analysis tools. The development of large, annotated datasets is crucial to training and validating these sophisticated algorithms.