MACHINE LEARNING & AI: A HIMSS EVENT
LAS VEGAS, NV - MARCH 5, 2018
Michael Gao is a data scientist at the Duke Institute for Health Innovation. He graduated from Duke University with a bachelor’s in Statistical Science and has since worked to integrate a variety of modern statistical and machine learning methods, including natural language processing and computer vision, into clinical practice at Duke University. He has worked on tools for the Medicare Shared Savings Program at the Duke University Health System, palliative care resource utilization, echocardiogram radiology reports, and transitions of care. He leads programs for undergraduates focused in data science for health and development of mobile applications for clinical research and continues to explore ways to leverage modern technologies in health system settings.
Despite excitement surrounding machine learning in healthcare, examples of full-fledged integration in day-to-day health system operations remains the exception, not the rule. Duke’s Institute for Health Innovation is in its third year developing and piloting machine learning technologies in clinical care.
To benefit from the full potential of machine learning, healthcare must step back from the trenches to acknowledge breakthroughs in technology, address barriers to progress, and critically reflect on the strategic priorities necessary to bring healthcare into a new digital age.
In this session, speakers will address the good, the bad, and the ugly when it comes to machine learning in healthcare.
Key discussion points:
One of the best ways learn is to network with your peers. This session will provide an opportunity to meet speakers and attendees who have similar privacy and security challenges and discuss solutions to those challenges.
Here's how it works:
Speakers will be stationed at different tables in the ballroom, and attendees can circulate and speak one-on-one or in groups with individual speakers. The speakers have been assigned different topics, but other topics can also be addressed.
Mingle, share and learn in this interactive environment.