AI in Medicine: Avoiding Hype and False Conclusions
AI in Medicine: Avoiding Hype and False Conclusions

Abstract: 

The widespread popularization of machine learning and its potential capabilities has increased the risk for exaggerated expectations and insufficiently critical thinking concerning the scaled implementation of AI in healthcare. Drawing on a well described framework for technology assessment this talk will step audience members through several examples of healthcare implementations of AI in order to highlight critical regulatory, data, policy, and human-factor issues required for optimal introduction of these technologies in clinical practice.

Bio: 

Michael E. Zalis, MD, is Chief of Clinical Solutions and Strategy for One Brave Idea, an incubator focused on care delivery innovation and cardiovascular genomics. He is also a part-time interventional radiologist at Massachusetts General Hospital, where he has been on faculty for many years. At One Brave Idea, he leads efforts to develop software products and clinical solutions, develops business strategy in the areas of cardiovascular genomics and insurance arbitrage, and works to improve operations for chronic disease management and digital phenotyping. Previously, he was a founder and Chief Medical Officer of QPID Health, Inc., a venture-backed medical informatics software company. Dr. Zalis holds a BA in biophysics from the University of Pennsylvania and an MD from the University of Virginia Health Sciences Center. He is a Fellow of the American College of Radiology.

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