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Evaluating AI Algorithm Accuracy in Predicting Complications and Outcomes of SMILE Eye Surgery
Led by Second Affiliated Hospital of Nanchang University · Updated on 2026-04-24
1250
Participants Needed
1
Research Sites
N/A
Total Duration
AI-Summary
What this Trial Is About
Researchers are evaluating the ability of a deep convolutional neural network CNN to predict complications and outcomes related to Small Incision Lenticule Extraction SMILE surgery, which is used to correct refractive errors in the eye. This observational, multi-center study aims to assess the diagnostic accuracy of the AI algorithm in identifying intraoperative complications such as opaque bubble layer OBL, negative pressure detachment, and black spots, which can affect surgery and recovery. The study is sponsored by the Second Affiliated Hospital of Nanchang University and focuses on improving prediction accuracy compared to human physicians. During the study, eyes that have undergone SMILE surgeries performed by experienced surgeons will be assessed using the AI diagnostic algorithm. The algorithms performance will be evaluated by measuring accuracy, area under the curve AUC, sensitivity, and specificity in predicting complications such as OBL area and progressive suction loss on the day of surgery, as well as postoperative outcomes including effective optical zone, refractive error, and central corneal thickness at day 7 and later timepoints. No treatment is administered as this is an observational study. Participants will be monitored through imaging and clinical data collected around the time of surgery and during follow-up visits up to day 90. Researchers will analyze the algorithms ability to predict surgical complications and postoperative results to determine its real-world utility. The primary outcomes include the AUROC values for various predictions on days 0 and 7, while secondary outcomes focus on sensitivity and specificity at multiple time points. The study includes adults aged 18 to 45 years with stable myopia and excludes those with other eye conditions or systemic diseases. Total participation length varies by individual.
CONDITIONS
Brief Title
Diagnostic Efficacy of CNN in Predicting Intraoperative Complications and Postoperative Outcomes in SMILE
Research Team
J
Jian Xiong, docter
F
Fu Gui, docter
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