Validation of the Utility of Strabismus Intelligent Diagnostic System

Sun Yat-sen University

Status: Unknown

Conditions: Strabismus; Ophthalmological Disorder

Treatments: Drug: Strabismus diagnostic system.

Study type: Observational

Funder types: Other

Identifiers

NCT04416776

SIDS-2020

Details and patient eligibility

About

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.

Enrollment: 323 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

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.

Trial design

323 participants in 1 patient group

Eligible patients for AI test

Description:

Device: strabismus diagnostic system.

Treatment:

Drug: Strabismus diagnostic system.