Simple, Mobile-based Artificial Intelligence AlgoRithms in the Detection of Diabetic ReTinopathy (SMART) Study

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

UNKNOWN

Total Enrollment

900 participants

Study Classification

OBSERVATIONAL

Study Start Date

2018-07-11

Study Completion Date

2018-10-31

Brief Summary

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

This is an observational cross sectional study aimed to evaluate the performance of the artificial intelligence algorithm in detecting any grade of diabetic retinopathy using retinal images from patients with diabetes.

Related Clinical Trials

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

Evaluation of NeoRetina Artificial Intelligence Algorithm for the Screening of Diabetic Retinopathy at the CHUM

NCT04699864

Diabetic Retinopathy Diabetic Macular Edema Diabetic Maculopathy

RECRUITING NA

A Blinded, Self-control Trial to Evaluate an Artificial Intelligence Based CAD System for Diabetic Retinography

NCT03973762

Diabetic Retinopathy

COMPLETED NA

Expansion of Integrated AI Solution for Diabetic Retinopathy Screening in Thailand

NCT05527535

Diabetic Retinopathy

UNKNOWN

Biomarkers of Diabetic Retinopathy Progression

NCT01607190

Type 2 Diabetes Mellitus Mild Nonproliferative Diabetic Retinopathy

COMPLETED

Shanghai Beixinjing Diabetic Eyes Study

NCT03571217

Diabetic Retinopathy Visual Impairment Diabetic Maculopathy

UNKNOWN

Detailed Description

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

Conditions

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

Diabetic Retinopathy

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

CROSS_SECTIONAL

Interventions

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

diabetic retinopathy

This is an observational study of patients with diabetes. Patients undergoing routine care will undergo retinal imaging using a nonmydriatic fundus camera. The images will be run on an artificial intelligence (AI) algorithm. The diagnosis of the artificial intelligence algorithm will be compared to the image diagnosis given by the ophthalmologists. The ophthalmologists will be blinded to the diagnosis of the AI and vice versa. The data will be analyzed to evaluate the performance of the AI.

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

1. Patients with type 1 or type 2 diabetes mellitus
2. Ages 18 and above
3. Male and female

Exclusion Criteria

1. Persistent visual impairment in one or both eyes;
2. Subjects with corneal opacities and advanced cataract.
3. History of retinal vascular (vein or artery) occlusion;
4. Subject is contraindicated for fundus photography (for example, has light sensitivity);
5. Subject is currently enrolled in an interventional study of an investigational device or drug;
6. Subject has a condition or is in a situation which in the opinion of the Investigator, might confound study results, may interfere significantly with the subject's participation in the study, or may result in ungradable clinical reference standard photographs.

Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No