Kidney disease identification using artificial intelligence and retinal photographs in people with diabetes
Not Applicable
- Conditions
- Health Condition 1: E112- Type 2 diabetes mellitus with kidney complications
- Registration Number
- CTRI/2024/04/065141
- Lead Sponsor
- European Foundation for the Study of Diabetes
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot Yet Recruiting
- Sex
- Not specified
- Target Recruitment
- 0
Inclusion Criteria
1. Data of individuals with type 2 diabetes aged = 18 years who have provided written informed consent for use of their anonymised data.
2. Data of individuals with and without diabetic kidney disease
3. Individuals who have clear retinal images
4. Retinal images with and without diabetic retinopathy changes
Exclusion Criteria
1.Unclear retinal images due to media opacities
2.Clinical and image data of those who have not provided consent for use of anonymized data
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Development of deep learning algorithm for prediction of kidney disease using retinal images among type 2 diabetesTimepoint: 1 year
- Secondary Outcome Measures
Name Time Method Real time validation deep learning algorithm developed for prediction of kidney disease using retinal imagesTimepoint: 6 months