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Artificial Intelligence-assissted Glaucoma Evaluation (AGE)

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ClinicalTrials.gov Identifier: NCT03268031
Recruitment Status : Recruiting
First Posted : August 31, 2017
Last Update Posted : September 6, 2018
Sponsor:
Collaborator:
Chinese Academy of Sciences
Information provided by (Responsible Party):
xiulan zhang, Sun Yat-sen University

Brief Summary:
Glaucoma is currently the second leading cause of irreversible blindness in the world. Our study intends to combine clinical data of glaucoma patients in Zhongshan Ophthalmic Center with Artificial Intelligence techniques to create programs that can screen and diagnose glaucoma.

Condition or disease Intervention/treatment
Artificial Intelligence Glaucoma Diagnostic Test: Visual field test

Detailed Description:
Glaucoma is currently the second leading cause of irreversible blindness in the world, which brings heavy burden to human society. Compared to other ocular diseases, diagnostic process of glaucoma is complicated depends on multiple test results, including visual field test, OCT, etc. How to diagnose glaucoma correctly and fast has always been a hot topic in glaucoma researches. Artificial intelligence is used to study and develop theories and methods that can help simulate and extend human intelligence, which has been utilized in a lot of research fields such as automatic drive and medicine. The study intends to combine clinical data of glaucoma patients in Zhongshan Ophthalmic Center with Artificial Intelligence techniques to create programs that can screen and diagnose glaucoma.

Study Type : Observational
Estimated Enrollment : 5000 participants
Observational Model: Case-Only
Time Perspective: Cross-Sectional
Official Title: Development of Artificial Intelligence-assissted Diagnostic Program of Glaucoma
Actual Study Start Date : August 15, 2017
Estimated Primary Completion Date : September 1, 2019
Estimated Study Completion Date : January 1, 2020

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Glaucoma

Group/Cohort Intervention/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.
Diagnostic Test: Visual field test
Visual field test and OCT are commonly used essential tests to make accurate diagnosis of glaucoma.
Other Name: Optical coherence tomography

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.
Diagnostic Test: Visual field test
Visual field test and OCT are commonly used essential tests to make accurate diagnosis of glaucoma.
Other Name: Optical coherence tomography




Primary Outcome Measures :
  1. Accuracy of diagnosis by artificial intelligence program [ Time Frame: from August 2017 to February 2019 ]
    Accuracy of diagnosis by artificial intelligence program and compare this result with glaucoma specialists


Secondary Outcome Measures :
  1. Sensitivity of diagnosis by artificial intelligence program [ Time Frame: from August 2017 to February 2019 ]
    Sensitivity of diagnosis by artificial intelligence program

  2. Specificity of diagnosis by artificial intelligence program [ Time Frame: from August 2017 to February 2019 ]
    Specificity of diagnosis by artificial intelligence program



Information from the National Library of Medicine

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Ages Eligible for Study:   Child, Adult, Older Adult
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Sampling Method:   Non-Probability Sample
Study Population
Anyone who can complete visual field test and have BCVA>0.1 can be enrolled. We will collect visual field test result and OCT images of both glaucoma and non-glaucoma patients.
Criteria

Inclusion Criteria:

  1. BCVA>0.1
  2. able to complete reliable visual field test
  3. no history of intraocular surgery or fundus laser

Exclusion Criteria:

1. unable to complete visual field test


Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03268031


Contacts
Contact: Xiulan Zhang, Doctor 8613570166308 xiulan_z@qq.com
Contact: Fei Li, Doctor 8613602299295 283630360@qq.com

Locations
China, Guangdong
Zhongshan Ophthalmic Center Recruiting
Guangzhou, Guangdong, China, 510000
Contact: Xiulan Zhang, Doctor    8613570166308    xiulan_z@qq.com   
Sponsors and Collaborators
Sun Yat-sen University
Chinese Academy of Sciences
Investigators
Principal Investigator: Xiulan Zhang, Doctor Sun Yat-sen University

Publications of Results:
Responsible Party: xiulan zhang, Director of Clinical Research Center, Sun Yat-sen University
ClinicalTrials.gov Identifier: NCT03268031     History of Changes
Other Study ID Numbers: ProjectAGE
First Posted: August 31, 2017    Key Record Dates
Last Update Posted: September 6, 2018
Last Verified: September 2018
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No

Keywords provided by xiulan zhang, Sun Yat-sen University:
artificial intelligence
glaucoma

Additional relevant MeSH terms:
Glaucoma
Ocular Hypertension
Eye Diseases