Validation of a Smartphone-based Intelligent Diagnosis and Measurement for Strabismus
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Strabismus
- Sponsor
- Sun Yat-sen University
- Enrollment
- 300
- Locations
- 1
- Primary Endpoint
- The effectiveness of smartphone-based diagnosis
- Status
- Recruiting
- Last Updated
- 3 years ago
Overview
Brief Summary
The current measurement methods of strabismus include the corneal light reflection method, prism alternate covering, etc., which especially rely on the subjective experience of doctors, and there is a large error between different measurers, leading to serious underestimation of strabismus prevalence and insufficient care for strabismus patients. Here, the investigators established and validated an artificial intelligence system to achieve an automatic diagnosis of strabismus based on patient-sourced videos of programmatic cover tests. Three-dimensional reconstruction methods are used to digitize the parameters of head and eye positions. This system has been integrated into a smartphone platform to be further validated through hospital-based and population-based clinical trials.
Investigators
Haotian Lin
Clinical Professor
Sun Yat-sen University
Eligibility Criteria
Inclusion Criteria
- •The quality of facial videos should be clinically acceptable.
Exclusion Criteria
- Not provided
Outcomes
Primary Outcomes
The effectiveness of smartphone-based diagnosis
Time Frame: Baseline
The accurate and the area under curve of the smartphone-based diagnosis.
The consistency between manual and smartphone measurement
Time Frame: Baseline
Agreement between the manual and automated tests was represented in Bland-Altman plots and concordance correlation coefficients.