Diagnostic Efficacy of CNN in Predicting Intraoperative Complications and Postoperative Outcomes in SMILE
Diagnostic Efficacy of Convolutional Neural Network Based Algorithm in Predicting Intraoperative Complications and Postoperative Outcomes in Small Incision Lenticule Extraction
Second Affiliated Hospital of Nanchang University
1,250 participants
Jun 15, 2021
OBSERVATIONAL
Conditions
Summary
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
Inclusion Criteria6
- 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;
- Stable myopia for at least 2 years;
- No contact lenses wearing for at least 2 weeks.
Exclusion Criteria3
- 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.
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Interventions
The SMILE procedures collected would be assessed by the algorithm. The performance of the algorithm would be assessed, including accuracy, AUC, sensitivity and specificity.
Locations(1)
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NCT06204926