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AI-enabled medical devices have seen significant regulatory acceptance, with over 75% of FDA-approved devices in radiology as of August 2025.
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Deep learning algorithms have revolutionized image recognition, enabling AI systems to match or exceed human radiologists' accuracy in detecting abnormalities.
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AI applications in medical imaging are transforming workflows, enhancing diagnostic accuracy, and providing new insights into disease management.
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The review identifies four key imaging procedures where AI can automate or improve workflows: MRI cancer screening, CT lung screening, coronary stenting, and ultrasound-guided liver cryoablation.
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A structured literature review was conducted to assess AI's role in imaging, focusing on contemporary practices and regulatory developments from 2015 to 2025.
