Artificial Intelligence in Vitreoretinal Surgery: A Systematic Review of Current Applications and Future Directions.

Introduction To examine the current landscape of artificial intelligence (AI) applications in vitreoretinal (VR) diseases and surgery, with the aim of identifying knowledge gaps and guiding future directions in this rapidly evolving field.Methods Systematic review including original studies involving the use of AI and focusing on VR pathologies. A comprehensive electronic search of the literature was carried out in multiple databases.Results Thirty-seven studies were included. Most evaluated machine learning or deep learning models for preoperative prognostication using optical coherence tomography with or without clinical variables. Predictive performance for postoperative best-corrected visual acuity (BCVA) was high in several cohorts (R2 up to 0.80; area under the receiver operating characteristic curve [AUROC] > 0.95), with models consistently highlighting outer retinal biomarkers as key determinants of visual recovery after epiretinal membrane and macular hole surgery. For anatomical outcomes, deep learning models frequently achieved > 90% accuracy in predicting macular hole closure and retinal reattachment/reattachment-related endpoints. Intraoperative computer-vision systems demonstrated feasibility for real-time instrument detection and tracking, reporting precision above 90% in experimental or early clinical settings. Large language models showed moderate-to-high agreement with expert surgical planning (80-93%) and potential utility in education and workflow support; however, across domains, most studies were retrospective and single-center, with limited external validation.Conclusions AI may transform vitreoretinal surgery, from outcome prediction to intraoperative guidance and workflow support. Despite strong performance in research settings, broader clinical adoption requires prospective validation to ensure reliability, transparency, and real-world benefit.This study looked at how artificial intelligence (AI) is being used in diseases and surgeries of the back part of the eye, known as the vitreoretinal (VR) area. We reviewed studies that used AI to help predict surgical outcomes, guide surgery, or improve efficiency in eye care, and found that AI models could accurately predict how well patients would see after surgery and whether the retina would heal properly. Some systems could even track surgical tools in real time, helping surgeons during operations. AI chatbots also showed promise in supporting doctors with planning and education. However, most studies were based on past data and small samples, meaning these tools are not yet ready for everyday use. Future research needs to test AI in real-world settings to make sure it is accurate, safe, and truly helpful for both patients and eye surgeons.