Artificial Intelligence for Screening of Multiple Corneal Diseases

T

Tianjin Eye Hospital

Status

Enrolling

Conditions

Deep Learning, Corneal Disease, Screening

Treatments

Diagnostic Test: Cornea diseases diagnosed by artificial intelligence algorithm

Study type

Observational

Funder types

Other

Identifiers

NCT06211218
KY-2023083

Details and patient eligibility

About

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.

Enrollment

3,000 estimated patients

Sex

All

Volunteers

No Healthy Volunteers

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.

Trial design

3,000 participants in 1 patient group

Cornea diseases diagnosed by artificial intelligence algorithm
Treatment:
Diagnostic Test: Cornea diseases diagnosed by artificial intelligence algorithm

Trial contacts and locations

1

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Central trial contact

Yan Huo, Master

Data sourced from clinicaltrials.gov

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