OphthalmopathyNCT03766737
Validation of the Utility of an Intelligent Visual Acuity Diagnostic System for Children
A study testing An intelligent visual acuity diagnostic system for children in people with Ophthalmopathy and Artificial Intelligence, run by Sun Yat-sen University at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 1 month to 14 yearsHealthy volunteers can take part
- Conditions the study is for
- Ophthalmopathy, Artificial Intelligence
- What is being tested?
- An intelligent visual acuity diagnostic system for children
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteChina
- Study dates
- 20 May 2018to 20 Jul 2018
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 1 month to 14 years
- All sexes
- Healthy volunteers accepted
- Child
Who may be able to join
- Paediatric patients from eye clinic written informed consents provided
Who cannot join
None listed.
Trial locations and contacts
1 site in 1 country.
China1 site
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong, 510000
About this study
Official title: Validation of the Utility of an Intelligent Visual Acuity Diagnostic System for Children: Using a Human-in-the-loop Artificial Intelligence Paradigm
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.
- Conditions
- Ophthalmopathy, Artificial Intelligence
- Being tested
- An intelligent visual acuity diagnostic system for children
- Keywords
- Vision Disorders
- Medical subject headings
- Eye Diseases, Vision Disorders
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
An intelligent visual acuity diagnostic system for childrenDevice
An artificial intelligence to make evaluation and of children's vision.
| Study group | Role | What they receive |
|---|---|---|
| Eligible patients for AI test. | Other | Device: An intelligent visual acuity diagnostic system for children. An artificial intelligence to evaluate children's vision. Receives: Device: An intelligent visual acuity diagnostic system for children |
What is being measured
The primary outcome is the main question the study is designed to answer.
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Measured: Up to 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Dec 2018
- Study start20 May 2018
- Primary completion20 Jul 2018
- Study completion20 Jul 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for OphthalmopathyStudies of the same condition, open and under way.
- More trials run by Sun Yat-sen UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 50 participants (actual)
Sponsor and investigators
- Lead sponsor
- Sun Yat-sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Haotian Lin, Sun Yat-sen University
- Investigators
- Lin Haotian, M.D, Ph.D, Principal investigator, Zhongshan Ophthalmic Center, Sun Yat-sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03766737
- Sponsor's protocol ID
- CCPMOH2018-China-12
- Status last verified
- Dec 2018
- First submitted
- 5 Dec 2018
- Last updated
- 6 Dec 2018
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 6 Dec 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of the Utility of an Intelligent Visual Acuity Diagnostic System for Children: Using a Human-in-the-loop Artificial Intelligence Paradigm
- ClinicalTrials.gov ID
- NCT03766737
- Acronym / sponsor ID
- CCPMOH2018-China-12
- Conditions
- Ophthalmopathy, Artificial Intelligence
- Keywords
- Vision Disorders
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 50 participants (actual)
- Lead sponsor
- Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 20 May 2018 (actual)
- Primary completion
- 20 Jul 2018 (actual)
- Study completion
- 20 Jul 2018 (actual)
- First posted
- 6 Dec 2018 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Eligible patients for AI test. | Other | Device: An intelligent visual acuity diagnostic system for childrenDevice: An intelligent visual acuity diagnostic system for children. An artificial intelligence to evaluate children's vision. |
Who may qualify
- Ages
- 1 month to 14 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child
Key inclusion criteria (1 listed)
- Paediatric patients from eye clinic written informed consents provided
Key exclusion criteria (0 listed)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| An intelligent visual acuity diagnostic system for childrenAn artificial intelligence to make evaluation and of children's vision. | Device | Eligible patients for AI test. |
Primary outcome
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Time frame: Up to 5 years
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Dec 2018.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Lin Haotian, M.D, Ph.D principal investigator
Zhongshan Ophthalmic Center, Sun Yat-sen University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing An intelligent visual acuity diagnostic system for children in people with Ophthalmopathy and Artificial Intelligence, run by Sun Yat-sen University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 0 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 6 Dec 2018. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system. (time frame: Up to 5 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Dec 2018; AzTrials last refreshed its copy on 7 Nov 2026.