Professor David Clifton


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Job title: Associate Professor
Division: Department of Engineering Science
Organisation: University of Oxford
Tags: Fellowship: HT Challenge Award
Related theme: Digital economy Healthcare technologies ICT


Prof. Clifton is an Associate Professor 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. His research focuses on the development of machine learning for healthcare technologies.

My Fellowship

Healthcare systems world-wide are struggling to cope with the demands of ever-increasing populations in the 21st-century, where the effects of increased life expectancy and the demands of modern lifestyles have created an unsustainable social and financial burden. However, ever-increasing quantities of complex data concerning all aspects of healthcare are being stored, throughout the life of a patient. These include electronic health records (EHRs) now active in many hospitals, and large volumes of data being collected by patient-worn sensors.

The resulting rapid growth in the amount of data that is stored far outpaces the capability of clinical experts to cope. There is huge potential for using advances in computer science to use these huge datasets. This promises to improve healthcare outcomes significantly by allowing the development of new technologies for healthcare using the data.

This programme establishes a new activity focussed on developing the next generation of predictive healthcare technologies, exploiting the EHR using new methods in computer science. This work is in collaboration with a consortium of leading clinicians and healthcare companies - the primary aim is to develop the "Intelligent EHR", which will have applications in creating "early warning systems" to predict patient problems (such as heart failure), and to help doctors know which drug or treatment would best be used for each individual patient - by interpreting the vast quantities of data available in the EHR.

Motivation to Apply

Clifton applied for his EPSRC fellowship after becoming aware of the size and scale of the difficulties faced by healthcare systems worldwide - engineering and computer science have a key role to play in addressing these difficulties. The fellowship offers a stable platform of support to build a strong research activity in this important area, and where the emphasis on career development and researcher training was especially appealing.

Career benefits of Fellowship

The support offered by the EPSRC has been transformative – in addition to providing key investment in enabling a research team to grow, it is also intended to form the basis for further grant applications. In the first year of the fellowship, three further EPSRC programmes have been awarded to develop the core healthcare technologies developed within the main fellowship, in addition to partnership funding from the Bill & Melinda Gates Foundation and the Wellcome Trust. The Computational Health Informatics (CHI) Lab at Oxford has rapidly grown to become a team of 15 post-doctoral researchers and 10 doctoral students.

Advice for future applicants

An EPSRC fellowship application is an opportunity to step outside the limited bounds of conventional funding streams and to state exactly what it is that, in an ideal world, one would research given the freedom that such a fellowship provides. The duration and flexibility of the award are sufficient to be able to "think big", and to develop the core technologies that subsequent, targeted proposals then build upon.