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Artificial Intelligence for Detecting Diabetic Changes in Eye

Developing and validating an artificial intelligence based model for diabetic retinopathy - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2024/01/061607
Enrollment
1000
Registered
2024-01-18
Start date
Unknown
Completion date
Unknown
Last updated
2024-01-22

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: E08-E13- Diabetes mellitus

Interventions

Intervention1: NIL: NIL Control Intervention1: NIL: NIL

Sponsors

All India Institute of Medical Sciences
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: PATIENTS of diabetes mellitus, cooperative for fundus photography

Exclusion criteria

Exclusion criteria: Not giving consent, Presence of any media opacity in the eye which may degrade the quality of the fundus image, Presence of significant ptosis or lid abnormalities hampering image capture

Design outcomes

Primary

MeasureTime frame
To evaluate the sensitivity, specificity, and accuracy of the AI solution in the detection and referral of diabetic retinopathy using retinal images captured from patients visiting the AIIMS eye centre.Timepoint: BASELINE—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactDr Rohan Chawla

All India Institute of Medical Sciences

dr.rohanrpc@gmail.com09891052939

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026