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Deep learning based automated detection and grading of diabetic retinopathy for screening programme

Deep learning based automated detection and grading of diabetic retinopathy for screening programme

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR-SON-17010692
Enrollment
Unknown
Registered
2017-02-20
Start date
2017-03-01
Completion date
Unknown
Last updated
2017-04-18

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

Conditions

diabetes retinopathy

Interventions

diabetic retinopathy:mark lesion
Without diabetic retinopathy:none

Sponsors

Shanghai Sixth People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 85 Years

Inclusion criteria

Inclusion criteria: (1) aged 18 years old or older; (2) diabetes mellitus; (3) without advanced cataracts or significant media opacity; (4) able to provide informed consent.

Exclusion criteria

Exclusion criteria: (1) unable to undergo a complete examination; (2) with a disease affecting retinal function, including glaucoma and wet AMD.

Design outcomes

Primary

MeasureTime frame
accuracy of diagnosis;—

Secondary

MeasureTime frame
accuracy of grading;—

Countries

China

Contacts

Public ContactQiang Wu

Shanghai Sixth People's Hospital Affiliated to Shanghai JiaoTong University

wyansh@163.com+86 021 24056111

Outcome results

None listed

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