A committee of experts from top U.S. medical centers and research institutes is harnessing NVIDIA-powered federated learning to evaluate the impact of federated learning and AI-assisted annotation to train AI models for tumor segmentation. 

Society for Imaging Informatics and Medicine (SIIM) Machine Learning Tools and Research Subcommittee is a group of clinicians, researchers and engineers that aims to advance the development and application of AI for medical imaging. NVIDIA is a member of SIIM, and has been collaborating with the committee on federated learning projects since 2019. 

Publish Date

Sep 20, 2024

Topic

  • Artificial Intelligence
  • Data Sets & Management
  • Machine Learning Challenges
  • Open Source
  • Radiology
  • Research

Resource Type

  • Blog

Audience Type

  • Clinician
  • Imaging IT
  • Researcher/Scientist
  • Student Member in Training (SMIT)

Visit This Resource

Related Resources

Resource

Teaching AI for Radiology Applications: A Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM

Oct 1, 2025

In a groundbreaking collaboration led by the SIIM Machine Learning Education Subcommittee, the American Association of Physicists in Medicine (AAPM), Radiological Society of North America (RSNA), and Society for Imaging Informatics in Medicine (SIIM) are proud to announce the simultaneous co-publication of “Teaching AI for Radiology Applications: A Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM” in these three flagship journals: Medical Physics, Radiology: Artificial Intelligence, and the Journal of Imaging Informatics in Medicine (JIIM).

The society-endorsed syllabus outlines critical competencies for four key groups: clinical users, technology purchasers, clinical collaborators, and AI developers. Designed as a flexible framework, it allows institutions to adapt content while ensuring consistent instruction on AI fundamentals, clinical integration, regulatory requirements, and ethical considerations.

Resource

Multi-Agent AI and Ethics in Radiology: Navigating the Trust Crisis in Advanced Medical Systems
(Part 1)

Sep 9, 2025

Part 1: The Medical AI Background: From Simple Tools to Complex Systems Picture this: you’re a radiologist examining a chest…

Resource

Multi-Agent AI and Ethics in Radiology: Navigating the Trust Crisis in Advanced Medical Systems
(Part 2)

Sep 9, 2025

Part 2: Framework, Regulation & Future Directions Additions Ethical Considerations in Medical AI Deployment The deployment of multi-agent AI systems…