Ophthalmological Disorder, Strabismus
Conditions
Brief summary
Strabismus affects approximately 0.8%-6.8% of the world's population and appears by the age of 3 years in 65% of affected individuals. Manual measurement of deviation is often laborious and highly dependent on the experience of the specialist and the cooperation of the patients. Current strabismus evaluation technologies are heavily dependent on model eyes. Here, the investigators use deep learning to develop an artificial intelligence (AI) platform consisting of three deep learning (DL) systems to screen strabismus, evaluate deviation and propose a surgical plan based on corneal light-reflection photos. The investigator also conduct clinical trial to validate its versatility in clinical practice.
Interventions
DRUGStrabismus diagnostic system.
An AI platform based on corneal light-reflection photos to facilitate the diagnosis and angle evaluation of strabismus and to provide advice for surgical planning.
Sponsors
Sun Yat-sen University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Patients in the outpatient clinic of strabismus department.
Exclusion criteria
* Patients or their parents diagree to participate in the trial. * Patients with blepharoptosis. * Patients can't facing forward or lacking fixation.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The proportion of accurate, mistaken and miss detection of the diagnostic system. | up to 3 years |
Countries
China
Contacts
Primary ContactKeli Mao, M.D
Outcome results
None listed