The SIIM Machine Learning and Research Committees are pivotal in advancing the organization’s strategy to position imaging informaticists at the forefront of discovery and innovation in medical imaging informatics. Their goals include fostering a collaborative research community and disseminating findings through various channels, including the Journal of Imaging Informatics in Medicine (JIIM). With AI/ML being the hottest area of medical imaging research, both committees have been targeting machine learning initiatives, aiming to provide educational resources, create policies and tools to curate public datasets, and establish methods and procedures to perform and publish machine learning work in reproducible ways. This collection provides access to the recent papers published by these committees, with a promise of more to come!

Publish Date

Oct 4, 2024

Topic

  • Artificial Intelligence
  • Machine Learning Challenges
  • Radiology
  • Research

Resource Type

  • JIIM

Audience Type

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

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…

Resource

Liquid Foundation Models: Revolutionizing AI Adaptability and Efficiency

Aug 26, 2025

Introduction In the rapidly evolving landscape of artificial intelligence, a new paradigm has emerged that promises to address some of…