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Comparing Eye Specialist Diagnosis and Artificial Intelligence Output in Diabetic Retinopathy from retinal images

Comparison of the DRISTi -Artificial Intelligence System with Ophthalmologists Diagnosis for Diabetic Retinopathy Detection - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/12/099823
Enrollment
1500
Registered
2025-12-24
Start date
Unknown
Completion date
Unknown
Last updated
2026-01-12

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

Conditions

Health Condition 1: H350- Background retinopathy and retinalvascular changes

Interventions

Intervention1: Nil: Nil

Sponsors

Artelus Pvt Ltd
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: The following participants will be included in the study 1.Patients aged greater or equal to 18 years both male and female with documented diagnosis of diabetes mellitus (Type 1 or Type 2) 2.Patient willing to consent to participate in the study

Exclusion criteria

Exclusion criteria: The following participants will be excluded from the study 1.Eyes with known non-diabetic retinal pathology that could confound assessment (retinal vascular occlusions, retinal detachment, macular degeneration etc ) 2.Eyes with media opacity preventing adequate visualization of the retina (dense cataracts, vitreous hemorrhage, corneal opacity) 3.Fundus photographs of insufficient quality for grading due to insufficient focus, under or over exposed images, insufficient retinal field of coverage, large lens smudges, scratches, or other such imaging artifact

Design outcomes

Primary

MeasureTime frame
To compare the diagnostic accuracy (sensitivity and specificity) of the DRISTi algorithm in detecting more than mild diabetic retinopathy (MTM-DR) and vision-threatening diabetic retinopathy (VT-DR) against a reference standard of clinical assessment by ophthalmologistsTimepoint: Baseline

Secondary

MeasureTime frame
nilTimepoint: nil

Countries

India

Contacts

Public ContactJyothsna Rajagopal

ARTELUS-Artificial Learning Systems India Private Limited,

jyothsna.rajagopal@gmail.com09980949289

Outcome results

None listed

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