{"href":"http://player.captivate.fm/services/oembed?url=http%3A%2F%2Fplayer.captivate.fm%2Fepisode%2F65cf36d7-5306-4019-bb91-3dea1d0edd59","version":"1.0","provider_name":"Captivate.FM","provider_url":"https://www.captivate.fm","width":600,"height":200,"type":"rich","html":"","title":"AI Explainability: What that Means and Why it Matters in the Medical Device Industry","description":"What is AI explainability? Why does it matter in health care?\n\nOn today\u2019s episode, we have Marla Phillips, director of Xavier Health, who shares why AI will transform how the medical device industry operates. Xavier Health brings the FDA and pharmaceutical and medical device industries together in a collaborative setting to break down barriers and improve patients\u2019 health.\n\nOvercome the media-generated hype and fear of AI to discover its benefits when using it responsibly. We can do better with it, than without it.\n\nSOME OF THE HIGHLIGHTS OF THE SHOW INCLUDE:\n\n\u25cf AI Explainability: Part of transparency of how end user can have confidence in the outcome of AI. Explainability links credibility of input to the output.\n\n\u25cf AI has been around since the 1950s, but its use is new to some people. The AI Summit shows how it works.\n\n\u25cf Pivoting from being reactive to proactive: Advancing use of AI to identify correlations between data for improvement of the quality of products/patients.\n\n\u25cf Some devices have digital health components. There\u2019s movements around real-world data for information to go to manufacturers to evaluate performance.\n\n\u25cf Continuous Product Quality Assurance team encourages review and assessment of all the data. AI can be used to identify conditions that lead to failure.\n\n\u25cf Where is the data? GMP, non-GMP, financial, weather, and other kinds of data that impacts product quality. Use AI to take out garbage, find what\u2019s meaningful.\n\n\u25cf AI is a continuously learning system. How to evaluate it? How did it reach its outcome? How to demonstrate credibility? How to train algorhythm?\n\n\u25cf Challenges of implementing AI include figuring out how to demonstrate credibility of AI output when not using validation and not having access to electronic data.","thumbnail_width":300,"thumbnail_height":300,"thumbnail_url":"https://artwork.captivate.fm/55aa5987-5c21-44e2-9557-3b4d6832157c/d7b9168e-cebe-4907-8e6a-d231c326e255.jpg"}