FDA AI/ML Radiology Approvals - Basis for Quantum Neural Network Neuroimaging

Explore FDA approvals for AI/ML algorithms in radiology and their implications for quantum neural network (QNN) neuroimaging applications in this comprehensive talk. Learn about the FDA's approach to continuously learning algorithms, including SaMD Pre-Specifications (SPS) and Algorithm Change Protocol (ACP). Understand the principle of "Probable Benefit Greater Than Probable Risk" and the requirements for 510(k) Premarket submissions. Analyze specific Quantum Convolutional Neural Network Neuroimaging Applications and their potential compliance with FDA standards. Gain insights into the potential regulatory pathways for quantum algorithms in medical imaging, including 510(k) submissions and De Novo Classification. Examine the role of international standards organizations in shaping future quantum algorithm submissions to the FDA. Review key FDA AI/ML articles and previous discussions on FDA regulations for quantum machine learning in neuroimaging. Discover examples of FDA-approved deep learning algorithms in cardiovascular imaging, CT image reconstruction, and portable MR imaging systems.

FDA AI/ML Radiology Approvals, Basis for QNN Neuroimaging