Study on the Diagnostic Efficacy of ICL Selection and Prediction Depth Model Based on Eye Images

ConditionsPosterior Chamber Phakic Intraocular Lens Vault Deep Neural Network Myopia Anterior Chamber Angle

Trial statusRecruiting

Trial phaseNot listed

Trial typeObservational

Biological sexAll

Age18-45

SponsorSecond Affiliated Hospital of Nanchang University

About this trial

To evaluate the diagnostic efficacy of deep learning network model in implantable collamer lens selection and prediction in a multicenter cross-sectional study

Eligibility criteria

Qualifiers

Aged 18-45 years ;

Myopia, with or without astigmatism, annual diopter change ≤ 0.50 D for 2 consecutive years ;

Anterior chamber depth ≥ 2.80 mm ;

Corneal endothelial cell count ≥ 2000 / mm2, stable cell morphology ;

Disqualifiers

There were no other ocular diseases that significantly affected vision and / or systemic organic lesions that affected surgical recovery;

Have a history of corneal refractive surgery or intraocular surgery ;

Corneal endothelial cell count is low ;

Those with systemic diseases ;

Trial design

Treatments tested in this trial

AI diagnostic algorithm

Treatment groups

326 Participants

are divided into 1 treatment group

Sponsors and collaborators

Second Affiliated Hospital of Nanchang University

Lead sponsor

Source ClinicalTrials.gov