PATIENT-LEVEL BIG DATA

We have a long history of using large national datasets to understand and improve clinical care. In particular, we have experience in longitudinal data analysis along clinical pathways and across multiple treatment pathways. We lead the GlioCova project which gives a national view of brain tumour care, variation, costs and outcomes.

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We have developed a range of imaging-based AI tools to help analyse clinical data at scale. Our focus is on useful, robust applications of AI in clinical care. Recent examples include our development of an end-to-end pipeline to determine muscle mass in brain tumour patients, and showing that this predicts patient survival, and scalable approaches to clustering and predicting outcomes in patients.

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We are now applying this to using AI to improve clinical care pathways.