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Quantitative Assessment of Myopia Fundus Based on Artificial Intelligence

Quantitative Assessment of Myopia Fundus Based on Artificial Intelligence

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300071219
Enrollment
Unknown
Registered
2023-05-08
Start date
2022-08-01
Completion date
Unknown
Last updated
2023-06-12

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

Conditions

myopia

Interventions

Case Series (Cross-sectional):None
Cohort Study Group (Whether suffering from myopia, different degrees of myopia):None

Sponsors

Beijing Tongren Hospital, Capital Medical University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Patients diagnosed with high myopia (defined as spherical equivalent refraction (SER)= 26.0 mm).

Exclusion criteria

Exclusion criteria: 1. Poor picture definition, unable to complete image recognition and data extraction; 2. Fundus photographs of patients with ocular and systemic diseases could affect the quantitative assessment of ONH and PPA, such as all kinds of glaucoma, diabetes retinopathy, and age-related macular degeneration; 3. Photographs of patients with intraocular surgery history were excluded, including cataract surgery, surgery of intraocular collamer lenses, and posterior scleral reinforcement.

Design outcomes

Primary

MeasureTime frame
Parameters of myopia fundus (such as leopard spots, optic disc and vascular parameters, etc.);

Secondary

MeasureTime frame
Follow-up and prediction of myopia;

Countries

China

Contacts

Public ContactJin Zibing

Beijing Tongren Hospital, Capital Medical University/Beijing Institute of Ophthalmology

jinzibing@foxmail.com+86 18511019921

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 7, 2026