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Research on Feature Extraction Network and Risk Prediction Model based on Optical Coherence Tomography images of High Myopia

Research on Feature Extraction Network and Risk Prediction Model based on Optical Coherence Tomography images of High Myopia

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500104182
Enrollment
Unknown
Registered
2025-06-12
Start date
2024-07-01
Completion date
Unknown
Last updated
2025-06-16

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

Conditions

High Myopia

Interventions

Observation group:None

Sponsors

Shenzhen Eye Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients with monocular or binocular diopter <= -5.5D detected through computer refraction or subjective refraction examination.

Exclusion criteria

Exclusion criteria: 1.Those with significantly incorrect or missing demographic information upon consultation; 2.Those whose imaging data cannot be retrieved; 3. Those with poor quality imaging data due to severe opacity of the refractive media or other causes.

Design outcomes

Primary

MeasureTime frame
AUC curve;Accuracy;Positive rate;Negative rate;False positive rate;False negative rate;—

Secondary

MeasureTime frame
Sensitivity thermogram;—

Countries

China

Contacts

Public ContactLi Wangting

Shenzhen Eye Hospital

liwangting@hotmail.com+86 135 8056 1850

Outcome results

None listed

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