Machine Learning in Healthcare, 21 September 2015

Session
Monday, 21 September 2015
09:21 - 09:21
Duration: 1 min
Publication date: 07 Oct 2015
Location: NA, Balliol College, Oxford, United Kingdom
Part of event Machine Learning in Healthcare

About the session

Machine learning has revolutionised many fields. With ever-increasing quantities of data being collected routinely throughout the healthcare system, there is an urgent need to develop new technologies based on machine learning for turning these very large and complex datasets into interventions that improve patient outcomes. The Machine Learning in Healthcare seminar includes lectures from key researchers, exploring the latest approaches to developing the next generation of healthcare technologies. A corresponding book, with contributions from the speakers will be published by The IET.

Keywords:: Balliol college

Machine

big data

clinicians

engineers

healthcare

learning

oxford

patient care

technologies

volunteers

Channels

Communities

Health care

Speakers

Prof. Christopher Williams

University of Edinburgh, Research Supervisor
Prof. Chris Holmes

University of Oxford, Professor of Biostatistics

I moved to Oxford from Imperial College London in February 2004. At Imperial College I studied for my doctorate in Bayesian statistics, investigating novel nonlinear pattern recognition methods. This was followed by a post-doctoral position and then a lectureship at Imperial. Previous to this I worked in industry for a number of years researching in scientific computing, developing techniques for real-time pattern recognition models in defence and SCADA (Supervisory Control and Data Acquisition) systems. My current research is focussed on applications and statistical methods development in the genomic sciences and genetic epidemiology. I hold a programme leaders grant in Statistical Genomics from the Medical Research Council.
Dr James Hensman

University of Sheffield
Prof. Bart Vanrumste

KU Leuven

He received a Master in Electrical Engineering (ir.) from the Ghent University, Belgium in 1994. In 1998 he received a Master in Biomedical Engineering also from Ghent University. In 2001 he received a Ph.D. in Engineering (dr.) from the same institute. His Ph.D. work on ‘EEG Dipole Source Analysis in a Realistic Head Model’ was supervised by Prof. Ignace Lemahieu and Prof. Paul Boon. He worked as a Post-Doctoral Fellow from 2001 until 2003 at the Electrical & Computer Engineering Department of the University Of Canterbury, New Zealand under supervision of Prof. Philip J Bones and Prof. Richard D. Jones.From 2003 until 2005 he was Post-Doctoral Fellow at the Department of Electrical Engineering (ESAT) at KU Leuven. His supervisor was Prof. Sabine Van Huffel. In 2005 he was appointed Professor in the Engineering Technology Department at the “Katholieke Hogeschool Kempen” in Geel and the “Katholieke Hogeschool Limburg”, which have been integrated in the Faculty of Engineering Technology of KU Leuven. Bart Vanrumste currently teaches courses on Digital Signal Processing, Digital Image Processing and Medical Instrumentation. He is head of the Advanced Integrated Sensing Lab (AdvISe), associated member of the ESAT-STADIUS division and Principle Investigator of iMinds Future Health Department. His research interests is Decision Support in Healthcare in general and Ambient Assisted Living in particular. His current research activities focus among other on multimodal sensor integration for monitoring of older persons and patients with chronic illnesses at their homes. Bart Vanrumste has (co-)authored over 90 peer reviewed papers in international journals or conference proceedings. He is an active reviewer for many Biomedical Technology and Ambient Assisted Living journals. He also has been a reviewer for the IWT and STW.He was awarded for his contribution on the 9th World Congress of the International Society for Brain Electromagnetic Topography, the10th World Congress of the International Society for Brain Electromagnetic Topography and 4th International Conference on Bioelectromagnetism.Since 2013 he is chair of the IEEE Engineering in Medicine and Biology Benelux Chapter and member of the International Society for Bioelectromagnetism.
prof. Niels Peek

University of Manchester

I am a Reader in Health Informatics at the MRC Health eResearch Centre for North England (www.herc.ac.uk), University of Manchester.My background is in Computer Science and Artificial Intelligence. After completing my studies I received a PhD in Computer Science from Utrecht University in the Netherlands, and subsequently worked at the Department of Medical Informatics of the Academic Medical Center in Amsterdam, the Netherlands. Currently I have co-authored over 100 scientific publications in health informatics, artificial intelligence, and epidemiology.My research focuses on improving quality and safety of healthcare using methods and tools from the fields of informatics, statistics and artificial intelligence. From 2003 to 2014, I have led a large initiative on quality improvement in cardiac rehabilitation in the Netherlands (called CARDSS), which involved a collaboration between more than 30 hospitals, the Dutch patients’ organization for cardiovascular disorders, a large number of professional societies, several academic research groups and three healthcare IT companies.I have also co-organized international workshops on intelligent data analysis in biomedicine in 2005, 2006, and 2011. Currently I am chairing the working group on Data Mining and Big Data Analytics from the International Medical Informatics Association (IMIA), and the Artificial Intelligence in Medicine (AIME) board, which organizes an international conference on that topic every two years.
Prof. Maarten de Vos

University of Oxford
Prof. Suchi Saria

John Hopkins University, Computer Science Department, Assistant Professor
Dr David Clifton

University of Oxford, Department of Engineering , Lecturer

Dr Clifton is a tenure-track member of faculty in the Department of Engineering Science of the University of Oxford, and a Governing Body fellow of Balliol College, Oxford. He is a Research Fellow of the Royal Academy of Engineering.A graduate of the Department of Engineering Science, Dr Clifton trained in information engineering and was supervised by Professor Lionel Tarassenko CBE, Chair of Electrical Engineering. He 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 CHI lab.Dr Clifton teaches the undergraduate mathematics syllabus in Engineering Science, runs the graduate course in machine learning at the Oxford Centre for Doctoral Training in Healthcare Innovation, and teaches engineering policy at the Blavatnik School of Government, Oxford. He is a founding Associate Editor of the IEEE Journal of Biomedical & Healthcare Informatics (JBHI), an editor of Health Information Science & Systems, and has served as an Associate Editor of BMC Medical Informatics, and of the British Journal of Health Informatics & Monitoring (BJHIM). He is the Associate Director of the Oxford Centre for Affordable Healthcare (OxCAHT).
prof. Niels Peek

University of Manchester

I am a Reader in Health Informatics at the MRC Health eResearch Centre for North England (www.herc.ac.uk), University of Manchester.My background is in Computer Science and Artificial Intelligence. After completing my studies I received a PhD in Computer Science from Utrecht University in the Netherlands, and subsequently worked at the Department of Medical Informatics of the Academic Medical Center in Amsterdam, the Netherlands. Currently I have co-authored over 100 scientific publications in health informatics, artificial intelligence, and epidemiology.My research focuses on improving quality and safety of healthcare using methods and tools from the fields of informatics, statistics and artificial intelligence. From 2003 to 2014, I have led a large initiative on quality improvement in cardiac rehabilitation in the Netherlands (called CARDSS), which involved a collaboration between more than 30 hospitals, the Dutch patients’ organization for cardiovascular disorders, a large number of professional societies, several academic research groups and three healthcare IT companies.I have also co-organized international workshops on intelligent data analysis in biomedicine in 2005, 2006, and 2011. Currently I am chairing the working group on Data Mining and Big Data Analytics from the International Medical Informatics Association (IMIA), and the Artificial Intelligence in Medicine (AIME) board, which organizes an international conference on that topic every two years.

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