Back to resultsValidation of the Utility of an Intelligent Visual Acuity Diagnostic System for Children
Primary Purpose
Ophthalmopathy, Artificial Intelligence
Status
Completed
Phase
Not Applicable
Locations
China
Study Type
Interventional
Intervention
An intelligent visual acuity diagnostic system for children
Sponsored by
About this trial
This is an interventional diagnostic trial for Ophthalmopathy focused on measuring Vision Disorders
Eligibility Criteria
Inclusion Criteria:
- Paediatric patients from eye clinic written informed consents provided
Sites / Locations
- Zhongshan Ophthalmic Center, Sun Yat-sen University
Arms of the Study
Arm 1
Arm Type
Other
Arm Label
Eligible patients for AI test.
Arm Description
Device: An intelligent visual acuity diagnostic system for children. An artificial intelligence to evaluate children's vision.
Outcomes
Primary Outcome Measures
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Secondary Outcome Measures
Full Information
NCT ID
NCT03766737
First Posted
December 5, 2018
Last Updated
December 5, 2018
Sponsor
Sun Yat-sen University
1. Study Identification
Unique Protocol Identification Number
NCT03766737
Brief Title
Validation of the Utility of an Intelligent Visual Acuity Diagnostic System for Children
Official Title
Validation of the Utility of an Intelligent Visual Acuity Diagnostic System for Children: Using a Human-in-the-loop Artificial Intelligence Paradigm
Study Type
Interventional
2. Study Status
Record Verification Date
December 2018
Overall Recruitment Status
Completed
Study Start Date
May 20, 2018 (Actual)
Primary Completion Date
July 20, 2018 (Actual)
Study Completion Date
July 20, 2018 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Sun Yat-sen University
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes
5. Study Description
Brief Summary
Visual development during early childhood is a vital process. Examining the visual acuity of children is essential for the early detection of visual abnormality, but performing such an assessment in children is challenging. Here, the investigators developed a human-in-the-loop artificial intelligence (AI) paradigm that combines traditional vision examination and AI with integrated software and hardware, thus making the vision examination easy to perform. The investigator also establish a entity intelligent visual acuity diagnostic system based on the paradigm, and conduct clinical trial to validate if the diagnostic system can offsetting the shortcomings of human doctors.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Ophthalmopathy, Artificial Intelligence
Keywords
Vision Disorders
7. Study Design
Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
50 (Actual)
8. Arms, Groups, and Interventions
Arm Title
Eligible patients for AI test.
Arm Type
Other
Arm Description
Device: An intelligent visual acuity diagnostic system for children. An artificial intelligence to evaluate children's vision.
Intervention Type
Device
Intervention Name(s)
An intelligent visual acuity diagnostic system for children
Intervention Description
An artificial intelligence to make evaluation and of children's vision.
Primary Outcome Measure Information:
Title
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Time Frame
Up to 5 years
10. Eligibility
Sex
All
Minimum Age & Unit of Time
1 Month
Maximum Age & Unit of Time
14 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria:
Paediatric patients from eye clinic written informed consents provided
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Lin Haotian, M.D, Ph.D
Organizational Affiliation
Zhongshan Ophthalmic Center, Sun Yat-sen University
Official's Role
Principal Investigator
Facility Information:
Facility Name
Zhongshan Ophthalmic Center, Sun Yat-sen University
City
Guangzhou
State/Province
Guangdong
ZIP/Postal Code
510000
Country
China
12. IPD Sharing Statement
Learn more about this trial
Validation of the Utility of an Intelligent Visual Acuity Diagnostic System for Children
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