Identifying and understanding bias is vitally important for trustworthy machine learning in medical imaging. Ali Tejani, MD, describes how bias is often inadvertent, and its causes may surprise you.
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SIIM Collaborates with The MarkeTech Group on AI Adoption Survey
In the early fall of 2025, SIIM partnered with The MarkeTech Group to explore how hospital-based imaging administrators are approaching AI adoption in radiology. The MarkeTech Group manages imagePRO™, a…
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Teaching AI for Radiology Applications: A Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM
In a groundbreaking collaboration led by the SIIM AI Education Subcommittee (formerly Machine Learning Education Subcommittee), the American Association of…
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Multi-Agent AI and Ethics in Radiology: Navigating the Trust Crisis in Advanced Medical Systems
(Part 1)
Part 1: The Medical AI Background: From Simple Tools to Complex Systems Picture this: you’re a radiologist examining a chest…