Deep LearningNCT06211218
Artificial Intelligence for Screening of Multiple Corneal Diseases
An observational study of Deep Learning and Corneal Disease, run by Tianjin Eye Hospital at 1 site in China.
Trial summary
This study developed a deep learning algorithm based on anterior segment images and prospectively validated its ability to identify corneal diseases.The effectiveness and accuracy of this algorithm was evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and area under curve. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Deep Learning, Corneal Disease, Screening
- What is being tested?
- Cornea diseases diagnosed by artificial intelligence algorithm
- How many people
- 3,000 participants
- Where
- 1 siteChina
- Study dates
- 6 Dec 2020to 6 Dec 2024
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: The study population is derived from an anonymous database that contains health examination results of the general population.
Who may be able to join
- The quality of slit-lamp images should clinical acceptable.
- More than 90% of the slit-lamp image area including three main regions (sclera, pupil, and lens) are easy to read and discriminate.
Who cannot join
- 1）Insufficient information for diagnosis.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Tiajin Eye Hospital
Tianjin, Tianjin Municipality
About this study
Official title: Application of Deep Learning for Screening Multiple Corneal Diseases
This study developed a deep learning algorithm based on anterior segment images and prospectively validated its ability to identify corneal diseases.The effectiveness and accuracy of this algorithm was evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and area under curve.
- Conditions
- Deep Learning, Corneal Disease, Screening
- Being tested
- Cornea diseases diagnosed by artificial intelligence algorithm
- Medical subject headings
- Corneal Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Cornea diseases diagnosed by artificial intelligence algorithmDiagnostic test
An artificial intelligence algorithm was applied to diagnose cornea diseases from slit-lamp images.
| Study group | Role | What they receive |
|---|---|---|
| Cornea diseases diagnosed by artificial intelligence algorithm | Not described Receives: Diagnostic Test: Cornea diseases diagnosed by artificial intelligence algorithm |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area under curve
We used the receiver operating characteristic (ROC) curve and area under curve to examine the ability of this artificial intelligence algorism recognition and classification of corneal diseases.
Measured: 1 week
Sensitivity and specificity
We used sensitivity and specificity to examine the ability of this artificial intelligence algorism recognition and classification of corneal diseases.
Measured: 1 week
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Jan 2024
- Study start6 Dec 2020
- Primary completion6 Dec 2021
- Study completion6 Dec 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Deep LearningStudies of the same condition, open and under way.
- 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
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Tianjin Eye Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Yan Wang, Prof, Study chair, Tianjin Eye Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06211218
- Sponsor's protocol ID
- KY-2023083
- Status last verified
- Oct 2024
- First submitted
- 8 Jan 2024
- Last updated
- 4 Nov 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 4 Nov 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Application of Deep Learning for Screening Multiple Corneal Diseases
- ClinicalTrials.gov ID
- NCT06211218
- Acronym / sponsor ID
- KY-2023083
- Conditions
- Deep Learning, Corneal Disease, Screening
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Tianjin Eye HospitalUniversity, hospital or other
- Study start
- 6 Dec 2020 (actual)
- Primary completion
- 6 Dec 2021 (actual)
- Study completion
- 6 Dec 2024 (estimated)
- First posted
- 18 Jan 2024 (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.
This study developed a deep learning algorithm based on anterior segment images and prospectively validated its ability to identify corneal diseases.The effectiveness and accuracy of this algorithm was evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and area under curve.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Cornea diseases diagnosed by artificial intelligence algorithm | – | Diagnostic Test: Cornea diseases diagnosed by artificial intelligence algorithm |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- The study population is derived from an anonymous database that contains health examination results of the general population.
Key inclusion criteria (2 listed)
- The quality of slit-lamp images should clinical acceptable.
- More than 90% of the slit-lamp image area including three main regions (sclera, pupil, and lens) are easy to read and discriminate.
Key exclusion criteria (1 listed)
- 1）Insufficient information for diagnosis.
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 |
|---|---|---|
| Cornea diseases diagnosed by artificial intelligence algorithmAn artificial intelligence algorithm was applied to diagnose cornea diseases from slit-lamp images. | Diagnostic test | Cornea diseases diagnosed by artificial intelligence algorithm |
Primary outcome
Area under curve
Time frame: 1 week
We used the receiver operating characteristic (ROC) curve and area under curve to examine the ability of this artificial intelligence algorism recognition and classification of corneal diseases.
Sensitivity and specificity
Time frame: 1 week
We used sensitivity and specificity to examine the ability of this artificial intelligence algorism recognition and classification of corneal diseases.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Nov 2024.
- Individual participant dataSharing planned: Undecided
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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.
Yan Wang, Prof study chair
Tianjin Eye Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Deep Learning and Corneal Disease, run by Tianjin Eye Hospital 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 2 inclusion and 1 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: looking for participants now, as of the sponsor's last update on 4 Nov 2024. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Yan Huo, Master (13102118953, hy13102118953@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Area under curve (time frame: 1 week). The study lists 2 primary outcomes in all. 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 4 Nov 2024.