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Study on the Diagnostic Efficacy of ICL Selection and Prediction Depth Model Based on Eye Images
Sponsor: Second Affiliated Hospital of Nanchang University
Summary
To evaluate the diagnostic efficacy of deep learning network model in implantable collamer lens selection and prediction in a multicenter cross-sectional study
Official title: Diagnostic Efficacy of Deep Neural Network Algorithm Based on Preoperative Scheimpflug-based Anterior Segment Image for Implantable Collamer Lens Selection and Prediction
Key Details
Gender
All
Age Range
18 Years - 45 Years
Study Type
OBSERVATIONAL
Enrollment
326
Start Date
2021-01-02
Completion Date
2025-08-31
Last Updated
2025-08-22
Healthy Volunteers
Yes
Conditions
Interventions
AI diagnostic algorithm
The ICL procedures collected would be assessed by the algorithm. The performance of the algorithm would be assessed, including accuracy, AUC, sensitivity and specificity.
Locations (1)
The Second Affiliated Hospital of Nanchang University
Nanchang, Jiangxi, China