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Research on a New Intelligent Mobile Screening and Diagnosis Pattern for Ocular Diseases

Research on a New Intelligent Mobile Screening and Diagnosis Pattern for Ocular Diseases

Status
Not yet recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07003165
Enrollment
15000
Registered
2025-06-04
Start date
2025-07-31
Completion date
2029-05-31
Last updated
2025-06-04

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

Conditions

Age Related Macular Degeneration (ARMD), Cataract, Diabetic Retinopathy (DR), Ophthalmic Diseases (Specific Types Not Restricted), Refraction Error

Brief summary

The global distribution of primary ophthalmic medical resources is uneven, and the traditional eye disease screening model has problems such as low efficiency, high cost and limited coverage. With the development of artificial intelligence and other technologies, it provides technical support for the construction of intelligent mobile screening model for eye diseases. The investigator's team has developed the 5G intelligent ophthalmic vehicle and served tens of thousands of people in 108 cities nationwide, initially verifying the feasibility of the new intelligent mobile screening model. However, the application effect, acceptance and influencing factors of this model in different regions are not clear, and there is a lack of economic benefit analysis based on real-world data. In this study, the investigators will conduct a cross-sectional study of large-scale population screening for blinding eye diseases in grassroots areas through the smart mobile screening model, focusing on the screening effectiveness and cost-effectiveness of the smart mobile screening model, integrating real-world multimodal eye health data, developing multiple smart screening analysis models, and exploring its adaptability and direction of improvement in grassroots areas.

Interventions

None listed

Sponsors

Zhongshan Ophthalmic Center, Sun Yat-sen University
Lead SponsorOTHER

Study design

Observational model
ECOLOGIC_OR_COMMUNITY
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
7 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Age ≥ 7 years * Voluntary informed consent

Exclusion criteria

-Inability to complete the required examinations with the help of others due to old age, infirmity, poor general condition, etc.

Design outcomes

Primary

MeasureTime frameDescription
Cost-effectivenessBaseline,6months,12monthsIncremental Cost per True Positive Case Detected

Secondary

MeasureTime frame
Eye disease detection rateBaseline,6months,12months
Accuracy of multiple intelligent screening analysis modelsBaseline
Screening participation ratebaseline

Contacts

Primary ContactLin Haotian
haot.lin@hotmail.com86-13802793086
Backup ContactXiao Wei
xiaow33@mail2.sysu.edu.cn86-13535160850

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026