Abstract: Nearly 2500 years ago, Hippocrates called for the careful recording and sharing of evidence about patients and their illnesses.  While this charge sits at the foundation of modern medicine, large amounts of critical healthcare data still goes unrecorded, in contradiction to the Hippocratic school of medicine—and to the Hippocratic oath that all physicians recite upon receiving their medical degree.  I will discuss insights and efficiencies that can be gained in healthcare by collecting and analyzing large amounts of data about patients and their encounters with healthcare providers.  The methods leverage algorithms for learning and decision making, and infrastructure for the capture of electronic records that will become more commonplace over time.
 
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Biography:
Eric Horvitz is a Distinguished Scientist at Microsoft Research. He has pursued theoretical and practical challenges with sensing, learning, and decision making under uncertainty, with applications in human decision making and in computational systems that perceive, learn, and reason. He has served as President of the Association for the Advancement of Artificial Intelligence (AAAI) and is now the Immediate Past President of the organization. He is a fellow of the American Association for the Advancement of Science (AAAS) and of the AAAI.  He received his PhD and MD degrees at Stanford University. More information can be found athttp://research.microsoft.com/~horvitz.