Artificial Intelligence for Screening of Multiple Corneal Diseases

October 31, 2024 updated by: Tianjin Eye Hospital

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

3000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Tianjin
      • Tianjin, Tianjin, China
        • Recruiting
        • Tiajin Eye Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

The study population is derived from an anonymous database that contains health examination results of the general population.

Description

Inclusion Criteria:

  1. The quality of slit-lamp images should clinical acceptable.
  2. More than 90% of the slit-lamp image area including three main regions (sclera, pupil, and lens) are easy to read and discriminate.

Exclusion Criteria:

1）Insufficient information for diagnosis.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Cornea diseases diagnosed by artificial intelligence algorithm
Diagnostic test: Cornea diseases diagnosed by artificial intelligence algorithm
An artificial intelligence algorithm was applied to diagnose cornea diseases from slit-lamp images.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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.
1 week
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.
1 week

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Tianjin Eye Hospital

Investigators

  • Study Chair: Yan Wang, Prof, Tianjin Eye Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 6, 2020

Primary Completion (Actual)

December 6, 2021

Study Completion (Estimated)

December 6, 2024

Study Registration Dates

First Submitted

January 8, 2024

First Submitted That Met QC Criteria

January 8, 2024

First Posted (Actual)

January 18, 2024

Study Record Updates

Last Update Posted (Estimated)

November 4, 2024

Last Update Submitted That Met QC Criteria

October 31, 2024

Last Verified

October 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • KY-2023083

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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