Artificial Intelligence for Screening of Multiple Corneal Diseases

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

3000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-12-06

Study Completion Date

2024-12-06

Brief Summary

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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.

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Detailed Description

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Conditions

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Deep Learning Corneal Disease Screening

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

PROSPECTIVE

Study Groups

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Cornea diseases diagnosed by artificial intelligence algorithm

Intervention Type DIAGNOSTIC_TEST

An artificial intelligence algorithm was applied to diagnose cornea diseases from slit-lamp images.

Interventions

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Cornea diseases diagnosed by artificial intelligence algorithm

An artificial intelligence algorithm was applied to diagnose cornea diseases from slit-lamp images.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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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.