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Synthetic data for a health research programme

Authors: Stickland, Rachael; Almarzouq, Batool;

Synthetic data for a health research programme

Abstract

This talk will be given by the members of the Research Support Facility (RSF), supporting the Artificial Intelligence for Multiple Long-Term Conditions (AIM) programme of research. The RSF (The Alan Turing Institute, Swansea University, and the University of Edinburgh) is developing data standards, disseminating best practices, and building community around researchers, patients and the public involved in AI for multiple long-term conditions research. These research projects utilise large population health datasets to get sufficient size and coverage to address complex health questions. These population health datasets can be challenging to access and work with. This talk will cover the use-cases for creating synthetic health datasets, in the context of research studies such as this. This talk will describe our case study with the synthetic versions of the Clinical Practice Research Datalink (CPRD), and how this helps address goals of the AIM programme. 

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