RECRUITING

Pivotal Trial of Automated Artificial Intelligence (AI) Based System for Early Diagnosis of Diabetic Retinopathy

Description

In this pivotal trial, we aim to perform a prospective study to find the efficacy of iPredict-DR, an artificial intelligence (AI) based software tool on early diagnosis of Diabetic Retinopathy (DR) in the primary care and endocrinology clinics. DR is one of the leading causes of blindness in the United States and other developed countries. Every individual with diabetes is at risk of DR. It does not show any symptoms until the disease is progressed to advanced stages. If the disease is caught at an early stage, it can be prevented, managed, or treated effectively. Currently, screening for DR is done by the Ophthalmologists, which is limited to areas with limited availability. This is also time-consuming and expensive. All of these can be complemented by automated screening and set up the screening in the primary care clinics.

Conditions

DiabetesDiabetic Retinopathy
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Related Conditions:

DiabetesDiabetic Retinopathy

Study Overview

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Study Details

Study overview

In this pivotal trial, we aim to perform a prospective study to find the efficacy of iPredict-DR, an artificial intelligence (AI) based software tool on early diagnosis of Diabetic Retinopathy (DR) in the primary care and endocrinology clinics. DR is one of the leading causes of blindness in the United States and other developed countries. Every individual with diabetes is at risk of DR. It does not show any symptoms until the disease is progressed to advanced stages. If the disease is caught at an early stage, it can be prevented, managed, or treated effectively. Currently, screening for DR is done by the Ophthalmologists, which is limited to areas with limited availability. This is also time-consuming and expensive. All of these can be complemented by automated screening and set up the screening in the primary care clinics.

Pivotal Trial of Automated AI-based System for Early Diagnosis of Diabetic Retinopathy Using Retinal Color Imaging

Pivotal Trial of Automated Artificial Intelligence (AI) Based System for Early Diagnosis of Diabetic Retinopathy

Condition
Diabetes
Intervention / Treatment

-

Contacts and Locations

Richmond Hill

iHealthScreen Inc., Richmond Hill, New York, United States, 11418

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

For general information about clinical research, read Learn About Studies.

Eligibility Criteria

  • * Age of Subjects: Patients ≥ 22 years of age.
  • * Gender of Subjects: Both males and females will be invited to participate.
  • * Subjects with diabetes (A1C level ≥ 6.5).
  • * Subjects must be willing and are able to comply with clinic visit, understand the study-related procedures/provisions, and provide signed informed consent.
  • * Unable to understand the study, Our unable to or unwilling to sign the informed consent
  • * Previously diagnosed with macular edema, any form of diabetic retinopathy, radiation retinopathy, or retinal vein occlusion
  • * participants who are experiencing persistent vision loss, blurred vision, or other vision problems that should be evaluated by an eye care provider
  • * subjects whose retinal images were used in training, validating, or developing the device
  • * Currently participating in another investigational eye study or actively receiving investigational product for DR or DME.
  • * A condition that, in the opinion of the investigator, would preclude participation in the study;
  • * Contraindicated for imaging by fundus imaging systems used in the study because of hypersensitivity to light, recently underwent photodynamic therapy, or was taking medication that causes photosensitivity.

Ages Eligible for Study

22 Years to

Sexes Eligible for Study

ALL

Accepts Healthy Volunteers

Yes

Collaborators and Investigators

iHealthScreen Inc,

Alauddin Bhuiyan, PhD, PRINCIPAL_INVESTIGATOR, iHealthScreen Inc

Study Record Dates

2027-07-31