Data driven technologies

Programme stream(s): Cancer control / living with and beyond and cancer outcomes , Early detection / diagnosis and prognosis , Prevention
Programme session type(s): Specialist session

Chair: David Weller, University of Edinburgh, UK
Speaker: Andrew Morris, Health Data Research UK
Speaker: Alan Karthikesalingam, Deep Mind Health
Speaker: Eva Morris, University of Leeds, UK

16:35-18:35

Room: Carron

This session will provide an overview of the use of data science in cancer risk assessment, prevention, screening, early diagnosis and survivorship. Over the last ten to fifteen years there have been huge advances in data technology and cancer intelligence systems in the UK and around the world they are rapidly becoming more refined and more useful in clinical medicine and public health. This session will examine how data science is transforming the way we approach cancer control; techniques such as linkage and big data analysis, machine learning and artificial intelligence will be included, and the session will provide some practical examples of how we can use collect and use data more effectively.

Options and Opportunities for Health Data Science
Speaker: Andrew Morris
Affiliation: Health Data Research UK

Abstract:

Healthcare is arguably the last major industry to be transformed by the information age.  Deployments of information technology have only scratched the surface of possibilities for the potential influence of information and computer science on the quality and cost-effectiveness of healthcare. In this talk, the vision, objectives and scientific strategy of HDR UK will be discussed; specifically, the opportunities provided by computer science and “big data” to transform health care delivery models.  Examples will be given from nationwide research and development programmes that integrate electronic patient records with biologic and health system data. Two themes will be explored; specifically:How the size of the UK (65M residents), allied to a relatively stable population and unified health care structures facilitate the application of health informatics to support nationwide quality-assured provision of care.How population-based datasets and disease registries can be integrated with biologic information to facilitate (i) epidemiology; (ii) drug safety studies; (iii) enhanced efficiency of clinical trials through automated follow-up of clinical events and treatment response; and, (iv) the conduct of large-scale genetic, pharmacogenetics, and family-based studies essential for precision medicine