SK
Samuel Kadoury, Julie G. Hussin, Pascal Th\'eriault-Lauzier, Laurent L\'etourneau-Guillon, Rob Lewis, Adam McArthur, Gordon J. Harris, Houda Bahig, Pierre-Luc D\'eziel, Jay Kshirsagar, Jacob L. Jaremko, Julien Cohen-Adad, Jacques Delfrate, Robert Avram
· 1 min read
ResearcharXiv cs.CV
Lessons learned from deploying imaging AI with the open PACS-AI platform
arXiv:2609.26981v1 Announce Type: new
Abstract: 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.
Original source
This story was published by arXiv cs.CV and written by Samuel Kadoury, Julie G. Hussin, Pascal Th\'eriault-Lauzier, Laurent L\'etourneau-Guillon, Rob Lewis, Adam McArthur, Gordon J. Harris, Houda Bahig, Pierre-Luc D\'eziel, Jay Kshirsagar, Jacob L. Jaremko, Julien Cohen-Adad, Jacques Delfrate, Robert Avram. SyncAI.news shows a preview; the complete article is on the publisher's site.
Read the full story on arxiv.org
