Esotropia, Exotropia, Strabismus, Vertical Strabismus
Conditions
Keywords
Mobile health, Artificaial intelligence medicine, Pediatric ophthalmology
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.
Interventions
DIAGNOSTIC_TESTA new technology based on 3D reconstruction and deep learning algorithm to achieve an automatic diagnosis of strabismus based on patient-sourced videos of programmatic cover tests.
Digital ruler of strabismus
Sponsors
Sun Yat-sen University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
3 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
The quality of facial videos should be clinically acceptable.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The consistency between manual and smartphone measurement | Baseline | Agreement between the manual and automated tests was represented in Bland-Altman plots and concordance correlation coefficients. |
| The effectiveness of smartphone-based diagnosis | Baseline | The accurate and the area under curve of the smartphone-based diagnosis. |
Countries
China
Contacts
Primary ContactHaotian Lin, M.D., Ph.D
Backup ContactRuixin Wang, M.D., Ph.D
Outcome results
None listed