Diagnostic Efficacy of CNN in Predicting Intraoperative Complications and Postoperative Outcomes in SMILE

ConditionsDeep Convolutional Neural Network Small-incision Lenticule Extraction (SMILE) Surgery Intraoperative Complications Postoperative Outcomes

Trial statusRecruiting

Trial phaseNot listed

Trial typeObservational

Biological sexAll

Age18-45

SponsorSecond Affiliated Hospital of Nanchang University

About this trial

To evaluate the diagnostic efficiency of the neural network in predicting complications of Small Incision Lenticule Extraction in a multi-center cross-sectional study.

Eligibility criteria

Qualifiers

A condition in which the spherical equivalent refractive error of an eye is ≤-0.50 D when ocular accommodation is relaxed;

Age ≥18 years;

Spherical equivalent (SE) ≥-10.0D;

Corrected distance visual acuity (CDVA) ≥16/20;

Disqualifiers

The presence or history of eye conditions other than myopia and astigmatism, such as keratoconus or external eye injury;

A history of eye surgery;

The presence or history of systemic diseases.

Trial design

Treatments tested in this trial

AI diagnostic algorithm

Treatment groups

1,250 Participants

are divided into 1 treatment group

Sponsors and collaborators

Second Affiliated Hospital of Nanchang University

Lead sponsor

Hangzhou Huaxia Eye Hospital

Collaborator

Nanchang Bright Eye Hospital

Collaborator

Source ClinicalTrials.gov