Artificial Intelligence-assissted Glaucoma Evaluation (AGE)
Development of Artificial Intelligence-assissted Diagnostic Program of Glaucoma
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
-
-
Guangdong
-
Guangzhou, Guangdong, China, 510000
- Zhongshan Ophthalmic Center
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- BCVA>0.1
- able to complete reliable visual field test
- no history of intraocular surgery or fundus laser
Exclusion Criteria:
1. unable to complete visual field test
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Glaucoma patients
Glaucoma patients will take visual field test and OCT imaging of optic nerve area.
All of these data will be collected as source of machine learning.
|
Visual field test and OCT are commonly used essential tests to make accurate diagnosis of glaucoma.
Algorithms to classify Visual field and OCT tests would both be developed and verified.
|
|
Non-glaucoma participants
Non-glaucoma participants will take visual field test and OCT imaging of optic nerve area.
All of these data will be collected as source of machine learning.
|
Visual field test and OCT are commonly used essential tests to make accurate diagnosis of glaucoma.
Algorithms to classify Visual field and OCT tests would both be developed and verified.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Accuracy of diagnosis by artificial intelligence algorithm
Time Frame: from August 2017 to February 2021
|
Accuracy of diagnosis by artificial intelligence algorithm and compare this result with glaucoma specialists
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from August 2017 to February 2021
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Sensitivity of diagnosis by artificial intelligence algorithm
Time Frame: from August 2017 to February 2021
|
Sensitivity of diagnosis by artificial intelligence algorithm
|
from August 2017 to February 2021
|
|
Specificity of diagnosis by artificial intelligence algorithm
Time Frame: from August 2017 to February 2021
|
Specificity of diagnosis by artificial intelligence algorithm
|
from August 2017 to February 2021
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Xiulan Zhang, Doctor, Sun Yat-sen University
Publications and helpful links
General Publications
- Diprose W, Buist N. Artificial intelligence in medicine: humans need not apply? N Z Med J. 2016 May 6;129(1434):73-6.
- Quigley HA. Glaucoma. Lancet. 2011 Apr 16;377(9774):1367-77. doi: 10.1016/S0140-6736(10)61423-7. Epub 2011 Mar 30.
- Asaoka R, Murata H, Iwase A, Araie M. Detecting Preperimetric Glaucoma with Standard Automated Perimetry Using a Deep Learning Classifier. Ophthalmology. 2016 Sep;123(9):1974-80. doi: 10.1016/j.ophtha.2016.05.029. Epub 2016 Jul 7.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- ProjectAGE
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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