Talks:
Mihaela Van der Schaar
Medicine 2.0: Using Machine Learning to Transform Medical Practice and Discovery
Abstract
This talk will present my view of the transformation of medicine through the use of machine learning and some of my own contributions. This transformation is already being felt in every aspect of medicine: from clinical support for personalized diagnosis and prognosis to the estimation of individualized treatment effects without the need for clinical trials to medical discovery to the entire path of patient care. The heart of this transformation is the intelligent use of data. Machine learning cannot do medicine, but I envision a future in which machine learning will provide clinicians with actionable information: personalized risk scores, personalized treatment effects, personalized diagnostic and prognostic assistance, and recommendations.
In this talk, I will describe some of my work toward the realization of this future: developing novel machine learning methods and applying them in a wide variety of medical settings, including early warning systems for admission to intensive care, mortality and survival prediction and individual treatment effects for heart transplantation, and screening policies and practice for cancer. This work achieves enormous improvements over current clinical practice and over existing machine learning methods – but there is much more to be done.
About the lecturer
Mihaela van der Schaar is the Man Professor, Oxford-Man Institute, Department of Engineering Science, University of Oxford. She is also affiliated with the Alan Turing Institute and the Farr Institute of Health Informatics Research. Her main research interest is on machine learning and artificial intelligence for medicine. She is an IEEE Fellow (2009) and has been a Distinguished Lecturer of the Communications Society and the Editor in Chief of IEEE Transactions on Multimedia. She received an NSF CAREER Award, several best paper awards, 3 IBM Faculty Awards, and holds 33 US patents.