Development of Artificial Intelligence-assissted Diagnostic Program of Glaucoma
Trial Snapshot
- Phase
- Not Applicable
- Status
- Completed
- Sponsor
- Enrollment
- 10,800
- Locations
- 1
- Primary Endpoint
- Accuracy of diagnosis by artificial intelligence algorithm
Study Overview
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.
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 Design
- Study Type
- Observational
- Observational Model
- Case Only
- Time Perspective
- Retrospective
Eligibility Criteria
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •able to complete reliable visual field test
- •no history of intraocular surgery or fundus laser
Exclusion Criteria
- •unable to complete visual field test
Outcomes
Primary Outcomes
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
Secondary Outcomes
- Specificity of diagnosis by artificial intelligence algorithm(from August 2017 to February 2021)
- Sensitivity of diagnosis by artificial intelligence algorithm(from August 2017 to February 2021)
Investigators
Xiulan Zhang
Director of Clinical Research Center
Sun Yat-sen University