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Dry Eye Screening and Referral System

NCT04413370 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 518

Last updated 2022-04-25

No results posted yet for this study

Summary

Dry eye is one of the most common ocular surface diseases. Its pathogenic factors are related to multiple etiology. Because of the complexity of the pathogenesis of dry eye, the diversity of related examinations, and the inconsistency of symptoms and signs of dry eye patients, the diagnosis of dry eye has higher requirements on the professional technology and examination equipment of ophthalmologists.

The purpose of this study is to establish a case-control cohort of dry eye patients. Multimodal data will be collected from participants, including medical history information, ocular surface disease index scale (OSDI), anterior segment photography, and treatment outcome of dry eye patients. The correlation between the characteristics of anterior segment images and dry eye diagnosis will be explored by artificial intelligence algorithms. The purpose of this study was to develop an artificial intelligence dry eye screening and referral system.

Conditions

  • Dry Eye

Interventions

DIAGNOSTIC_TEST

Dry eye diagnostic test

The artificial intelligent dry eye screening platform

Sponsors & Collaborators

  • Sun Yat-sen University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-01-06
Primary Completion
2022-04-19
Completion
2022-08-01

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 NCT04413370 on ClinicalTrials.gov