A regular series of open invitation talks from leading voices in data science, AI, healthcare and those with lived experience dealing with multiple long-term conditions (MLTC). This seminar series is part of the AI for multiple long-term conditions: Research Support Facility project. 

About the event

The diversity of data and its scale and complexity are important factors to note when undertaking research related to the study of multiple long-term conditions. Demographics, socioeconomic indicators, and the condition data, when linked, provide a powerful, dynamic, and flexible research asset for the investigator. Allied to the realisation of the research benefits of such linked data is the need for hosting in a catalytic environment that securely fulfils the enabling function for the realisation of the research equity the data holds.

The presentation will outline the approach of the ‘Trusted Research Environment’ to provide publicly acceptable secure data linkage, the provision of a research environment replete with multiple technological data tools, an ability to support ‘team science’, and interoperability to allow the realisation of the potential of the data across this field of research. The growth of research in multiple long-term conditions requires environments to respond and ensure that platforms efficiently enable this research and learn and adapt to any challenges this scale of research may present.

Register now

Register now

By registering for the event, you are agreeing to the events code of conduct:
Events code of conduct | The Alan Turing Institute



Dave Chapman

Programme Manager, AI for Multiple long-term conditions Research Support Facility