Data, Health and Society:
Predicting and preventing disease
Lead: Prof Christopher Kipps
We are using data science to integrate multiple different data sources, enabling us to categorise, predict and prevent disease.
Health needs we are tackling
How can we use data science to integrate multiple data sources to predict, categorise and prevent disease?
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Identifying action signals for intervention: we are integrating highly diverse data sets such as ‘omic, periconceptual, and imaging data linked to the wider environmental context.
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Artificial intelligence (AI) early warning system: we are using AI to combine profiles of observable characteristics of patients with real-time data to inform clinical decision making.
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Predicting individual risk: we are optimising comparative data to predict individual risk, for example by using data on dementia, cardiac rhythms, and patient e-pathway management.