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Driving Digital Health Research with AI in Ophthalmology

Driving Digital Health Research with AI in Ophthalmology

Status
Active, not recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500114471
Enrollment
Unknown
Registered
2025-12-12
Start date
2026-01-01
Completion date
Unknown
Last updated
2025-12-15

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

Conditions

blinding eye diseases and systemic diseases

Interventions

Gold Standard:Blinding eye diseases diagnosed based on color fundus photography (CFP), and systemic diseases diagnosed through blood pressure measurement, blood tests, computed tomography (CT), or mag
Index test:The color fundus photograph is automatically analyzed by an artificial intelligence algorithm model, outputting detection results for blinding eye diseases and systemic diseases.

Sponsors

Chinese University of Hong Kong
Lead Sponsor

Eligibility

Sex/Gender
All
Age
50 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age 50 years or older. 2. Willingness to undergo ophthalmic imaging (e.g., fundus photography, OCT scans). 3. Ability to provide informed consent.

Exclusion criteria

Exclusion criteria: 1. Severe ocular comorbidities that may interfere with image acquisition or interpretation. 2. Inability to provide informed consent due to cognitive impairment or other reasons.

Design outcomes

Primary

MeasureTime frame
The accuracy, sensitivity, and specificity of the AI platform in detecting blinding eye diseases (e.g., glaucoma, diabetic retinopathy) and systemic diseases (e.g., Alzheimer's disease, cardiovascular diseases) compared to gold-standard clinical diagnoses.;

Secondary

MeasureTime frame
The generalizability of the AI platform for the detection of blinding eye diseases and systemic diseases across diverse imaging devices and clinical environments.; The effectiveness of the AI platform on clinical decision-making, including the rate of early detection and intervention for blinding eye diseases and systemic diseases.; The cost-effectiveness of the AI platform in reducing healthcare resource utilization and improving patient outcomes.;

Countries

China

Contacts

Public ContactZhang Yanlei

Department of Ophthalmology and Visual Sciences, Chinese University of Hong Kong

carolcheung@cuhk.edu.hk+852 3943 5831

Outcome results

None listed

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