How to orchestrate clinical AI algorithms in active worklists

Clinical AI tools are often deployed in isolation, requiring radiologists to view results in separate browser windows. True efficiency gains require embedding AI inside the main reading worklist.

HNVNS AI intercepts incoming scans and routes DICOM files through specialized classifiers before queue assignment. These models check for critical pathology, such as intracranial hemorrhages or pneumothorax.

If a positive flag is detected, the case is assigned a high-priority status and moved to the top of the unread queue, alerting on-duty radiologists in seconds.

AI markers and bounding coordinates are overlaid directly onto the diagnostic viewer canvas, helping the reader locate key anomalies without breaking their cognitive workflow.