- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04413370
Dry Eye Screening and Referral System
The Development of Artificial Intelligence Dry Eye Screening and Referral System
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.
Study Overview
Status
Conditions
Intervention / Treatment
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
-
-
Guangdong
-
Guangzhou, Guangdong, China, 510632
- Zhongshan Ophthalmic Center
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Subjects whose age are greater than or equal to 18 years old;
- Subjects who can cooperate with the inspection;
- Subjects who agree to participate in the study and sign the consent form.
Exclusion Criteria:
- Subjects who cannot do the inspection.
- Subjects who suffer from diseases that compromise the inspection.
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Severe Group
This group of subjects needed a referral to the hospital for further treatments.
|
The artificial intelligent dry eye screening platform
|
|
Mild group
This group of subjects was diagnosed with dry eye but can use artificial tears instead of further treatment.
|
The artificial intelligent dry eye screening platform
|
|
Follow-up group
This group of subjects had no dry eye symptoms and signs and belonged to the normal control group.
|
The artificial intelligent dry eye screening platform
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Area under the curve (severe)
Time Frame: up to 1 month
|
AUC values for predicting whether subject need to be referral or not.
|
up to 1 month
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Area under the curve (each group)
Time Frame: up to 1 month
|
AUC values for predicting whether subject can be accurately grouped into each of the four groups.
|
up to 1 month
|
|
Accuracy, true positive rate, and true negative rate
Time Frame: up to 1 month
|
The performance of this artificial platform.
|
up to 1 month
|
Collaborators and Investigators
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- Dry eye screening system
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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