FDA Recommendations for Artificial Intelligence/Machine Learning (AI/ML)-Enabled Device Software Functions

Are you an AI university researcher, software or biomedical engineer, software programmer, developer, executive, or start-up entrepreneur in the field of medical devices such as radiology, and plan on designing, marketing, or maintaining an FDA-compliant AI machine learning software for use in health care? Are you a regulatory affairs professional working on regulatory submissions to the FDA in the medical device space? Are you interested in entering the above fields of work of regulatory affairs, engineering, software, and AI development? Are you just interested in knowing your AI bill of rights as an
American? If you answered yes to any of the above, this webinar is for you. AI and machine learning software are used more and more in the healthcare industry. There are, as of 03 July 2023, 521 AI/machine learning enabled devices approved by the FDA. A major area where AI machine learning software is involved is in the field of radiology. For instance, AI software may automatically segment, quantify, and report on different cardiac function measurements from MR scans. AI machine learning software may be used for image viewing, processing, and analysis and support health care practitioners
with their surgical procedures or with diagnosis. What is required for FDA approval of AI machine learning software? What are the FDA’s expectations and concerns? FDA has determined that the marketing submission for AI machine learning software includes a predetermined change control plan for approval and the continued safe and effective performance of the AI/machine learning-enabled device software post-approval. This webinar will explore this topic.