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Validation of the Utility of Strabismus Intelligent Diagnostic System

NCT04416776 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 323

Last updated 2020-06-04

No results posted yet for this study

Summary

Strabismus affects approximately 0.8%-6.8% of the world's population and appears by the age of 3 years in 65% of affected individuals. Manual measurement of deviation is often laborious and highly dependent on the experience of the specialist and the cooperation of the patients. Current strabismus evaluation technologies are heavily dependent on model eyes. Here, the investigators use deep learning to develop an artificial intelligence (AI) platform consisting of three deep learning (DL) systems to screen strabismus, evaluate deviation and propose a surgical plan based on corneal light-reflection photos. The investigator also conduct clinical trial to validate its versatility in clinical practice.

Conditions

  • Ophthalmological Disorder
  • Strabismus

Interventions

DRUG

Strabismus diagnostic system.

An AI platform based on corneal light-reflection photos to facilitate the diagnosis and angle evaluation of strabismus and to provide advice for surgical planning.

Sponsors & Collaborators

  • Sun Yat-sen University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-09-01
Primary Completion
2020-06-10
Completion
2020-06-10

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 NCT04416776 on ClinicalTrials.gov