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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 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.
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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…
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Multi-Agent AI and Ethics in Radiology: Navigating the Trust Crisis in Advanced Medical Systems
(Part 2)
Part 2: Framework, Regulation & Future Directions Additions Ethical Considerations in Medical AI Deployment The deployment of multi-agent AI systems…
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Liquid Foundation Models: Revolutionizing AI Adaptability and Efficiency
Introduction In the rapidly evolving landscape of artificial intelligence, a new paradigm has emerged that promises to address some of…
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Discover Pathology-Focused Resources at SIIM
SIIM is committed to strategic technical leadership and education in digital pathology. We’re thrilled to offer a diverse array of…
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Imaging Informatics Career Matrix
Define, Compare, and Advance Your Imaging Informatics Knowledge Ready to grow your expertise in imaging informatics? This tool is designed…
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Use of AI in Cardiac CT and MRI: A Scientific Statement from the ESCR, EuSoMII, NASCI, SCCT, SCMR, SIIM, and RSNA
Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through…
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SIIM24 Annual Meeting Abstract Booklet
Dive into the cutting-edge innovations in imaging informatics with the SIIM24 Annual Meeting Abstract Booklet! This comprehensive publication includes all…