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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
Sponsor:
Information provided by (Responsible Party):
Haiyan Wang, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Brief Summary:
This study will develop an artificial intelligence (AI) program for the screening of glaucoma.

Condition or disease Intervention/treatment
Glaucoma Eye Diagnostic Test: Fundus Image

Detailed Description:

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.


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Study Type : Observational
Estimated Enrollment : 8000 participants
Observational Model: Case-Only
Time Perspective: Prospective
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

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Glaucoma

Group/Cohort Intervention/treatment
Fundus Image
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




Primary Outcome Measures :
  1. 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 ...

  2. 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 .



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
Both glaucoma and non-glaucoma patients who can complete fundus image test will be enrolled.
Criteria

Inclusion Criteria:

  • able to complete fundus images

Exclusion Criteria:

  • unable to complete fundus images

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): NCT03682783


Contacts
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Contact: Haiyan Wang, Ph.D. +86 15000096256 catherinecnc81@126.com
Contact: Kun Liu, Ph.D. +86 36126112 drliukun@sjtu.edu.cn

Locations
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China, Shanghai
Shanghai General Hospital
Shanghai, Shanghai, China, 200080
Sponsors and Collaborators
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Investigators
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Principal Investigator: Haiyan Wang, Ph.D. Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

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Responsible Party: Haiyan Wang, Attending of Ophthalmology, M.D. Ph.D., Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
ClinicalTrials.gov Identifier: NCT03682783     History of Changes
Other Study ID Numbers: 81300776
First Posted: September 25, 2018    Key Record Dates
Last Update Posted: September 25, 2018
Last Verified: September 2018

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

Keywords provided by Haiyan Wang, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine:
Artificial Intelligence; Glaucoma

Additional relevant MeSH terms:
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Glaucoma
Ocular Hypertension
Eye Diseases