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

NCT06204926 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1250

Last updated 2026-04-24

No results posted yet for this study

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.

Conditions

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

Interventions

DIAGNOSTIC_TEST

AI diagnostic algorithm

The SMILE procedures collected would be assessed by the algorithm. The performance of the algorithm would be assessed, including accuracy, AUC, sensitivity and specificity.

Sponsors & Collaborators

  • Hangzhou Huaxia Eye Hospital

    collaborator UNKNOWN

  • Nanchang Bright Eye Hospital

    collaborator UNKNOWN

  • Second Affiliated Hospital of Nanchang University

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
45 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2021-06-15
Primary Completion
2027-12-31
Completion
2027-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06204926 on ClinicalTrials.gov