Diabetic Retinopathy Screening
This dataset contains de-identified retinal fundus images captured using Remedio imaging systems, curated for the detection and grading of Diabetic Retinopathy (DR). It is standardized and quality-checked to support AI/ML model development, clinical research, and decision support, while ensuring complete exclusion of personally identifiable information (PII).
About Dataset
This dataset comprises de-identified retinal fundus images acquired from real-world, ground-level clinical settings using Remedio ophthalmic imaging systems, curated for the assessment and analysis of Diabetic Retinopathy (DR). The data is standardized, quality-checked, and structured to support clinical research, AI model development, and integration with interoperable healthcare systems, while ensuring no personally identifiable information (PII) is present.
Purpose of Dataset
The Dataset Is Designed To Enable The Development, Validation, And Benchmarking Of Ai/ml Models For Automated Detection And Grading Of Diabetic Retinopathy. It Supports Clinical Decision Support Systems, Advances Research In Ophthalmology And Medical Imaging, And Contributes To Scalable, Technology-driven Solutions For Early Diagnosis And Prevention Of Vision Loss.
Dataset Metadata
NA
India
Healthcare, Wellness and Family Welfare
Dr. Mona Duggal
Unstructured
Static
Static
N.A.
26/03/26 05:19:17
Restricted
Hosted
Primary
Activity Overview
0
0 
39 
14.45 MB
Tags
- ophthalmology
- Diabetic Retinopathy
- Retinal Fundus Imaging
- Medical Imaging Dataset
- Ophthalmology
- Artificial Intelligence in Healthcare
License Control
NA
DR Screening ( 1 directories )
DR_Screening
2 files, 1 directories
Data Quality Score Beta
Version Control
Version 1(14.45 MB)
- Mona Duggal·7 day(s) ago
- chevron_right
DR Screening
- chevron_right
DR_Screening
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