Strabismus Clinical Trial
Official title:
Validation of the Utility of Strabismus Intelligent Diagnostic System: A Clinical Trial
NCT number | NCT04416776 |
Other study ID # | SIDS-2020 |
Secondary ID | |
Status | Recruiting |
Phase | |
First received | |
Last updated | |
Start date | September 1, 2019 |
Est. completion date | June 10, 2020 |
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.
Status | Recruiting |
Enrollment | 323 |
Est. completion date | June 10, 2020 |
Est. primary completion date | June 10, 2020 |
Accepts healthy volunteers | No |
Gender | All |
Age group | N/A and older |
Eligibility |
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. |
Country | Name | City | State |
---|---|---|---|
China | Zhongshan Ophthalmic Center, Sun Yat-sen University | Guangzhou | Guangdong |
Lead Sponsor | Collaborator |
---|---|
Sun Yat-sen University |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | The proportion of accurate, mistaken and miss detection of the diagnostic system. | up to 3 years |
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