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Fundus Image Grading and Disease Detection

Screening Retinal Images Using Artificial Intelligence for Gradability and Morbidity

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2020/07/026415
Enrollment
4000
Registered
2020-07-07
Start date
Unknown
Completion date
Unknown
Last updated
2021-11-24

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

Conditions

Health Condition 1: E113- Type 2 diabetes mellitus with ophthalmic complications

Interventions

Intervention1: ScreenRad: This is a retrospective trial. The patients that underwent a color fundus photography via Visupac fundus camera were selected from 1st January 2019 to 31st December 2019. The

Sponsors

Gibbr Technologies Pvt Ltd
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: The images of both male and female patients have been taken into consideration who are 10+ years of age.

Exclusion criteria

Exclusion criteria:

Design outcomes

Primary

MeasureTime frame
The fundus images will be screened by the software and the if the images are gradable then the same will be sent for morbidity detectionTimepoint: 12 months—

Secondary

MeasureTime frame
The gradable images, thereafter, will be classified by the AI software if the image has particular morbidity.Timepoint: 12 months—

Countries

India

Contacts

Public ContactMr Jayanth Rasamsetti

Gibbr Technologies Pvt Ltd

jay@sgmoid.com9347987563

Outcome results

None listed

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