Simple, Mobile-based Artificial Intelligence AlgoRithms in the Detection of Diabetic ReTinopathy (SMART) Study
- Conditions
- Diabetic Retinopathy
- Registration Number
- NCT03572699
- Lead Sponsor
- Medios Technologies Pte. Ltd
- Brief Summary
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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 900
Inclusion Criteria
- Patients with type 1 or type 2 diabetes mellitus
- Ages 18 and above
- Male and female
Exclusion Criteria
- Persistent visual impairment in one or both eyes;
- Subjects with corneal opacities and advanced cataract.
- History of retinal vascular (vein or artery) occlusion;
- Subject is contraindicated for fundus photography (for example, has light sensitivity);
- Subject is currently enrolled in an interventional study of an investigational device or drug;
- 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.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Sensitivity and specificity of the AI in detecting any grade of diabetic retinopathy 3 months
- Secondary Outcome Measures
Name Time Method Sensitivity and specificity of the AI in detecting referable diabetic retinopathy (referable retinopathy defined as moderate non proliferative retinopathy or greater) 3 months Sensitivity and specificity of the AI in detecting sight threatening diabetic retinopathy (referable retinopathy defined as severe non proliferative retinopathy or greater) 3 months
Trial Locations
- Locations (1)
Diacon Hospital
🇮🇳Bangalore, India