Artificial Intelligence-assisted Glaucoma Screening (AIAGS)
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|ClinicalTrials.gov Identifier: NCT03682783|
Recruitment Status : Not yet recruiting
First Posted : September 25, 2018
Last Update Posted : September 25, 2018
|Condition or disease||Intervention/treatment|
|Glaucoma Eye||Diagnostic Test: Fundus Image|
We have realized that the glaucomatous optic neuropathy is irreversible. But if early detection and early intervention can be performed to control the development of the disease, it can greatly reduce the blindness rate of glaucoma, improve the life quality and physiological and mental health of patients, and alleviate the social burden. Therefore, screening and early diagnosis of glaucoma is the focus of glaucoma prevention.
China has a population of 1.3 billion, which greatly increase the difficulty of disease screening. In recent years, the intersection of artificial intelligence (AI) technology and modern medicine has made efficient and rapid disease screening possible.
|Study Type :||Observational|
|Estimated Enrollment :||8000 participants|
|Official Title:||The Development of Artificial Intelligence-assisted Glaucoma Screening Program|
|Estimated Study Start Date :||October 1, 2018|
|Estimated Primary Completion Date :||October 1, 2020|
|Estimated Study Completion Date :||October 30, 2021|
Glaucomatous and Non-glaucomatous fundus images that have been taken from the last 5 years in Shanghai General hospital.
Diagnostic Test: Fundus Image
Fundus image of optic nerve
- The specificity of the algorithm for diagnosing glaucoma [ Time Frame: from January 2020 to March 2021 ]The specificity of the algorithm for diagnosing glaucoma will be calculated ...
- The sensitivity of the algorithm for diagnosing glaucoma [ Time Frame: from January 2020 to March 2021 ]The sensitivity of the algorithm for diagnosing glaucoma will be calculated .
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): NCT03682783
|Contact: Haiyan Wang, Ph.D.||+86 email@example.com|
|Contact: Kun Liu, Ph.D.||+86 firstname.lastname@example.org|
|Shanghai General Hospital|
|Shanghai, Shanghai, China, 200080|
|Principal Investigator:||Haiyan Wang, Ph.D.||Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine|