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This webinar was initially presented in March 2023 at CSMD2023.

on-demand webinar practical points in creating clinical evidence for ai samd medical devices this presentation highlights standards that can be followed to bring an added layer of rigor to the development and documentation of ai/ml-based medical devices.

Artificial intelligence (AI)- and machine learning (ML)-based medical devices, once a dream of science fiction writers, have firmly established their place in the market and will continue to gain in popularity in the coming months and years. With uses ranging from virtual assistance to image analytics to robotic-assisted surgeries, manufacturers have only begun to explore the utility and value of these devices.

Such rapid innovation, however, can cause severe regulatory headaches. The relatively controlled and documented methods applied to R&D of conventional medical devices are not traditionally practiced in the highly agile environment of AI/ML algorithm development. This presentation will highlight standards that can be followed to bring an added layer of rigor to the development and documentation of AI/ML-based medical devices. In addition, it will cover Good Machine Learning Practices that will aid manufacturers in designing proper validation and clinical testing procedures to enable a smoother regulatory submission process.

Bethany Chung, Ph.D., RAC
Principal Regulatory Scientist

Bethany Chung

Bethany has a Ph.D. in biomedical engineering and loves all things quantitative. She has more than 10 years of experience with medical devices in the clinical space. Prior to joining the regulatory world, she was a clinical researcher specializing in ML and AI-based devices, and she is currently in the Clinical and Post Market Practice at RQM+.

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