PACS integration determines whether imaging AI output appears where radiologists can review it without latency, duplicate work, or interface friction.
PACS fit matters because a strong imaging AI model can still fail if its output arrives late, sits in a separate dashboard, or adds extra clicks during interpretation. The finding should appear where radiologists already review studies and manage their worklist.
This page explains the deployment questions behind PACS integration: where AI output is displayed, how latency is handled, how failed runs are surfaced, how findings are documented, and whether the integration supports review instead of distracting from it.
PACS integration determines whether imaging AI findings are usable inside real radiology review rather than isolated in a disconnected system.