It seems like everywhere we look computers are running more and more of the world around us. In healthcare, we have seen an astounding level of hype surrounding the use of artificial intelligence in image recognition, personalised treatment, form filling in and diagnostic technologies. What are the potential applications for AI in health and life sciences, but also the barriers to its adoption and practical implementation?
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About the speakers
Professor David Clifton is an Associate Professor in the Department of Engineering Science of the University of Oxford. He is also a Research Fellow of the Royal Academy of Engineering and founding Associate Editor of the IEEE Journal of Biomedical & Healthcare Informatics (JBHI).
David spent four years as a post-doctoral researcher in biomedical engineering at Oxford before his appointment to the faculty, at which point he started the Computational Health Informatics Lab (CHI). In 2017, the CHI Lab opened its second site in Suzhou (China), with support from the Chinese government.
His research focuses on the development of "big data" machine learning for tracking the health of complex systems. His previous research resulted in patented systems for jet-engine health monitoring, used with the engines of the Airbus A380, the Boeing 787 "Dreamliner", and the Eurofighter Typhoon. Since 2008, he has translated his work into the biomedical context for healthcare applications. He has worked on Visensia, the world's first FDA-approved multivariate patient monitoring system, and the SEND system, which is now used to monitor 20,000 patients each month in the NHS. His research has been commercialised via university spin-out companies OBS Medical, Oxehealth, and Medyc, in addition to collaboration with multinational industrial bodies.
In 2016, Professor Clifton was awarded a Grand Challenge award from the UK Engineering and Physical Sciences Research Council, which is a personal award that provides long-term strategic support for nine "future leaders in healthcare".