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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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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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…