A real-world deployment in Oslo showed that iterative radiologist feedback through the NeoMedSys platform improved an AI brain bleed detector’s performance. In a three-month clinical roll-out, VIOLA-AI’s sensitivity increased from 79.2% to 90.3%, and AUC rose from 0.873 to 0.949 after incorporating clinician feedback signals. The update approach underscores that deployment monitoring and model adaptation can materially change performance outside benchmark settings. For AI imaging teams and health systems, the results highlight an execution path for moving from static model validation to continuous performance improvement with clinical loop integration.