Cornea diseases diagnosed by artificial intelligence algorithm
Cornea diseases diagnosed by artificial intelligence algorithm: An artificial intelligence algorithm was applied to diagnose cornea diseases from slit-lamp images.
Study 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.
Eligibility
Sex
ALL
Min age
—
Max age
—
Healthy volunteers
No
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.
Primary outcome measure(s)
Area under curve — 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 — 1 week We used sensitivity and specificity to examine the ability of this artificial intelligence algorism recognition and classification of corneal diseases.
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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