Artificial Intelligence-assissted Glaucoma Evaluation

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Total Enrollment

10800 participants

Study Classification

OBSERVATIONAL

Study Start Date

2017-08-15

Study Completion Date

2020-02-01

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

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.

Related Clinical Trials

Explore similar clinical trials based on study characteristics and research focus.

Diagnostic Efficacy of CNN in Differentiation of Visual Field

NCT03759483

Diagnositic Efficacy of Deep Convolutional Neural Network in Differentiation of Glaucoma Visual Field From Non-glaucoma Visual Field

COMPLETED

Artificial Intelligence-assisted Glaucoma Screening (AIAGS)

NCT03682783

Glaucoma Eye

UNKNOWN

Matching Glaucoma With Impaired Cognition

NCT03695224

Morbidity of Primary Open Angle Glaucoma

UNKNOWN

Glaucoma Screening Using An Artificial Intelligence Assisted Clinical Model in Singapore's Diabetic Eye Screening Program

NCT07243665

Glaucoma

NOT_YET_RECRUITING NA

Effect of OXSIGHT Smart Glasses on Patients With Advanced Glaucoma

NCT04434612

Advanced Glaucoma

UNKNOWN NA

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

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.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Artificial Intelligence Glaucoma

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

CASE_ONLY

Study Time Perspective

RETROSPECTIVE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

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.

Visual field and OCT tests

Intervention Type DIAGNOSTIC_TEST

Visual field test and OCT are commonly used essential tests to make accurate diagnosis of glaucoma. Algorithms to classify Visual field and OCT tests would both be developed and verified.

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.

Visual field and OCT tests

Intervention Type DIAGNOSTIC_TEST

Visual field test and OCT are commonly used essential tests to make accurate diagnosis of glaucoma. Algorithms to classify Visual field and OCT tests would both be developed and verified.

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

Visual field and OCT tests

Visual field test and OCT are commonly used essential tests to make accurate diagnosis of glaucoma. Algorithms to classify Visual field and OCT tests would both be developed and verified.

Intervention Type DIAGNOSTIC_TEST