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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.

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Health needs we are tackling


How can we use data science to integrate multiple data sources to predict, categorise and prevent disease? 

  • 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.

  • 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.

  • 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.


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