CompletedNot Applicable

Diagnostic Efficacy of CNN in Differentiation of Visual Field

China437 participantsStarted 2019-03-15

Plain-language summary

Glaucoma is currently the leading cause of irreversible blindness in the world. The multi-center study is designed to evaluate the efficacy of the convolutional neural network based algorithm in differentiation of glaucomatous from non-glaucomatous visual field, and to assess its utility in the real world.

Who can participate

Age range

18 Years

Sex

ALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion criteria

. Age≥18;
. Informed consent obtained;
. Diagnosed with specific ocular diseases;
. Able to perform visual field test

Questions worth asking your doctor

Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.

1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?

Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.

Questions for the trial coordinator

The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.

1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?

A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.

What they're measuring

AUC value of convolutional neural network in differentiation of Glaucoma visual field from non-glaucoma visual field

Timeframe: from Jan 2019 to Jan 2020

Trial details

NCT IDNCT03759483

SponsorSun Yat-sen University

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2019-12-31

View on ClinicalTrials.gov More Diagnositic Efficacy of Deep Convolutional Neural Network in Differentiation of Glaucoma Visual Field From Non-glaucoma Visual Field trials