The agreement or disagreement between AI findings and radiologist-reported diagnoses.
Positive Concordance is the AI’s ability to correctly identify positive cases while Negative Concordance is AI’s ability to correctly classify negative cases.
PPV is the proportion of AI detected cases that area accurately determined as positives NPV are the proportion of AI detected cases that are correctively identified as negative.
Drift Reporting and Trends track the Accuracy and FI scoring over time of each algorithm in use to identify long- term tending bias or tolerance change.
Augmented Findings Rate (AFR) refers to the relative or absolute increase in correctly identified diagnoses due to the implementation of an AI system compared to standard diagnostic practice.
Prevalence refers to the proportion of imaging studies that truly contain a specific pathology within the dataset used to evaluate AI diagnostic performance.
The AIQ Score in AI monitoring is a composite metric that quantifies the intelligence level of an AI system by benchmarking its diagnostic accuracy, consistency, and adaptability against expert radiologist performance.
AI is changing radiology.
It’s driving earlier detection, easing workloads, and boosting diagnostic accuracy.
But concerns remain: reliability, transparency, clinical proof
Without a clear, standardized way to measure AI performance, adoption stalls, and trust wavers.
“In partnership with Bialogics, we can offer clinicians and healthcare administrators, not only a comprehensive suite of Business Intelligence and Clinical Intelligence tools but a means to meaningfully evaluate clinical AI performance on local data and gain insights into their AI investment.”
