Tired of hearing technical experts talk about machine learning algorithms and not understanding what they are saying? This webinar is intended for regulatory attorneys advising clients developing algorithms for regulated or nearly regulated uses. It will provide a broad understanding of the machine learning models including supervised, unsupervised, and deep learning. The webinar will also cover the importance of and challenges in mitigating explicit and implicit racial bias negatively impacting Blacks and ethnic minority groups in algorithmic design. The webinar will include a case study using machine learning on data from FDA on 510(k) summaries and include the use of natural language processing (i.e., how Alexa understands humans).

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Bradley Merrill Thompson, Partner, Epstein Becker & Green, PC
Jana Delfino, Assistant Director for Medical Imaging and Digital Health, Division of Imaging, Diagnostics and Software Reliability (DIDSR), OSEL, CDRH, FDA

Summer Learning Series

The Summer Learning Series brings the top thinkers and leaders of our industry to speak on a broad array of topics essential to the food and drug law professional, covering matters that perhaps we all wish we knew a bit more about as we work and converse with clients, colleagues, and the FDA. Join us this June through July and build foundation in the following subjects:


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On-demand webinar content is sent via email as soon as we are able to process and verify your order. This usually occurs within 1 business day.


On-demand content can be played back on most devices.


CLE credit is not currently available for pre-recorded sessions.

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