AI Misclassification
The AI model's high negative predictive value helped reduce false-negative screening failures. The AI algorithm misclassified 9.5% of cases as referable diabetic retinopathy. False positives may increase unnecessary referrals, burden healt…
1 sources - 5 claims
The AI model's high negative predictive value helped reduce false-negative screening failures. The AI algorithm misclassified 9.5% of cases as referable diabetic retinopathy. False positives may increase unnecessary referrals, burden health systems and cause patient anxiety. AI-assisted screening has potential but requires careful integration because of misclassification risk. False negatives are more dangerous because they can miss treatment referrals and increase preventable vision loss risk.