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Comparison of Artificial Intelligence ophthalmologist with in detecting Diabetic Retinopathy

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

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/10/096073
Enrollment
2500
Registered
2025-10-14
Start date
Unknown
Completion date
Unknown
Last updated
2025-11-17

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 Intervention2: Nil: Nil Intervention3: Nil: Nil Intervention4: Nil: Nil

Sponsors

Artelus Pvt Ltd
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: patient visiting hospital for diabetic screening or retinal evaluation

Exclusion criteria

Exclusion criteria: Images of patients which are un-gradbale

Design outcomes

Primary

MeasureTime frame
Primary outcome measures 1.Sensitivity and specificity of the DRISTi algorithm for detecting more than Mild DR and vision threartening DR compared to the reference standard Timepoint: only at baseline since this is a cross sectional single observation study—

Secondary

MeasureTime frame
nilTimepoint:—

Countries

India

Contacts

Public ContactPradeep Walia

ARTELUS-Artificial Learning Systems India Private Limited,

j.rajagopal@artelus.ai09980949289

Outcome results

None listed

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