Artificial Intelligence for Screening of Multiple Corneal Diseases

Recruiting now

Conditions studied: Deep Learning, Corneal Disease, Screening

In brief

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.

Key facts

Study ID

NCT06211218

Run by

Tianjin Eye Hospital

People needed

3000

Starts

2020-12-06

Expected to finish

2024-12-06

Last updated by the study team

2024-11-04

Who can join

Age: any. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• 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.

You may not qualify if…

• 1）Insufficient information for diagnosis.

Where it is running

• Tiajin Eye Hospital — Tianjin, Tianjin Municipality, China (enrolling)

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.