Machine learning and AI in medicine – Part 1

For years relegated to science fiction, as exemplified when the HAL 9000 had a speaking role in 2001: A Space Odyssey, artificial intelligence (AI) now has become practical reality and in medicine, a long-hoped-for remedy in areas from pathology to electronic medical records. Yet, artificial intelligence, which encompasses machine learning and other functions, has limitations. In this episode, learn about the current state of artificial intelligence and what it can realistically achieve for your practice. Guest speaker: Shannon Sims, MD, PhD Vice President Data Intelligence and Interoperability Vizient Moderator: Tomas Villanueva, DO, MBA, FACPE, SFHM Associate Vice President Clinical Resources Vizient Show Notes [00:56] Understanding concepts around AI [02:28] Two main functions of AI [03:33] Importance of prescriptive analytics [04:26] Enabling clinicians make better decisions [05:13] Machine learning and EMRs [06:10] AI and the coronavirus [07:52] Structural challenges [09:01] AI and quality [10:09] Role of clinicians in developing solutions [11:04] Successes and limitations Links | Resources: Machine Learning in Medicine (NEJM—April 4, 2019) Click here HYPE Randomized Clinical Trial Click here Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data (JAMA Internal Medicine—Nov 2018) Click here On Deep Learning for Medical Image Analysis (JAMA—Sept 18, 2018) Click here Artificial Intelligence in Health Care: Will the Value Match the Hype? (JAMA—June 8, 2019) Click here Artificial Intelligence in Health Care: A Report from the National Academy of Medicine (JAMA—Feb 11, 2020) Click here Artificial Intelligence: Promise, Pitfalls and Perspective (JAMA—June 23/30, 2020) Click here Subscribe Today! Apple Podcasts Spotify Android Google Podcasts Stitcher RSS Feed