DeepMind Blog

Enabling a new model for healthcare with AI co-clinician

Researching the path to AI-augmented care and development of an AI co-clinician.

arXiv AI
Jul 29

"We'll have to see how it works": An interview study to understand collaborative practices in interdisciplinary artificial intelligence and healthcare research

arXiv:2311. 18424v3 Announce Type: replace-cross Abstract: Developing artificial intelligence (AI) algorithms for healthcare is a collaborative effort, bringing data scientists, clinicians, patients and other stakeholders together.

By Rafael Henkin, Elizabeth Remfry, Duncan J. Reynolds, Megan Clinch, Michael R. Barnes
arXiv Computer Vision
Sep 24

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

The article reports on the deployment of imaging AI across six hospitals using the open, self‑hosted PACS‑AI platform. It emphasizes that the main limitation is not model accuracy but the infrastructure needed to route studies, display results, collect feedback, and audit runs. In one center, angiography models processed 84.8% of jobs, with failures mainly due to missing diagnostic views, and 78.1% of clinician ratings were positive.

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
arXiv AI
Jun 2

Empathic and agentic artificial intelligence in nursing: perspectives on a human-centered framework for cancer care navigation in the United States

arXiv:2606. 00010v1 Announce Type: cross Abstract: For patients experiencing cancer, nurse navigation can ease the burden of complex care by enhancing coordination of health services and patient outcomes.

By Tyra Girdwood, Saba Kheirinejad, Parnian Kheirkhah Rahimabad, Brianna M. White, Robert L Davis, David L Schwartz, Arash Shaban-Nejad