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Lessons learned from deploying imaging AI with the open PACS-AI platform

Occurred
Sep 22, 2026
Published
Sep 22, 2026
Source
arXiv

Summary

We describe deploying imaging AI at six hospitals through PACS-AI, an open self-hosted platform. The binding constraint is not model accuracy but infrastructure to route studies, display results, capture feedback, and audit what runs. At one center, angiography models completed 515 of 607 jobs (84.8%); failures reflected absent diagnostic views, and 78.1% of 638 clinician ratings were positive. Publishing honest readiness levels for every model is itself a governance practice.

Classification

Category confidence: 70%
Severity confidence: 90%

Rationale: This is a research paper discussing AI deployment lessons, not a safety incident.

Classifier: Qwen/Qwen3.5-35B-A3B-FP8

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