Artificial Intelligence (AI) - Assisted Visual Impairment Screening Model: Community-based Implementation and Evaluation of Performance, Feasibility and Costs.
NCT ID: NCT06877988
Last Updated: 2025-05-14
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
400 participants
INTERVENTIONAL
2024-06-27
2026-03-31
Brief Summary
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* Can the AI-assisted screening model improve screening and referral accuracy compared to the current traditional screening approach?
* Does the AI-assisted model enhance operational efficiency and reduce healthcare costs in a community setting?
Researchers will compare the AI-assisted model with the current traditional screening approach to assess its impact on screening accuracy, operational efficiency, and cost-effectiveness.
Participants will:
* Undergo vision screening using either the AI-assisted model or the traditional model.
* Provide feedback on the acceptability of the screening approach.
* Contribute to evaluating the feasibility and costs associated with each screening method.
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
DIAGNOSTIC
DOUBLE
Study Groups
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AI-assisted
Participants will undergo visual impairment screening using AVIRI model (AI for Disease-related Visual Impairment Screening Using Retinal Imaging). This intervention involves automated fundus image analysis through artificial intelligence to screen and identify individuals with high probability of visual impairment.
AI
Retinal photography-based deep learning algorithm for detection of disease-related visual impairment cases
Traditional
Participants will receive visual impairment screening using the traditional screening model, which involves optometrists performing initial assessments, followed by referral decisions based on manual fundus image evaluation.
No interventions assigned to this group
Interventions
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AI
Retinal photography-based deep learning algorithm for detection of disease-related visual impairment cases
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
50 Years
ALL
Yes
Sponsors
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Institute of High Performance Computing (IHPC), A*STAR Research Institutes
UNKNOWN
National University Polyclinics, Singapore
OTHER
Singapore Eye Research Institute
OTHER
Responsible Party
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Tham Yih Chung
Principal Investigator
Locations
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Pioneer Polyclinic
Singapore, Singapore, Singapore
Countries
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Central Contacts
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Clarine Ho
Role: CONTACT
Facility Contacts
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Other Identifiers
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2024/2297
Identifier Type: -
Identifier Source: org_study_id
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