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AI for diabetes - enhancing diagnosis and personalised care

Diabetes is a growing global epidemic, with cases rising from 200 million in 1990 to 830 million in 2022, according to the WHO. Type-2 diabetes (T2D), which is predominantly lifestyle related, affects almost 10% of the global population and is expected to rise exponentially over the next 20 years. Mortality rates from diabetes have been increasing since 2000, and gestational diabetes is also a growing concern, currently affecting around 1 in 20 pregnancies in the UK.

Preventing and detecting T2D early is essential to avoid additional complications, reduce long-term damage, and ultimately save lives.

Clinicians are moving beyond a ‘one-size-fits-all’ approach, seeking to better classify subtypes of T2D using readily available clinical parameters to deliver personalised care.

This project will provide student the opportunity to leverage AI to transform T2D care by combining heterogeneous datasets to deliver:

  • improved diagnosis and prediction of disease progression,
  • improved, personalised treatment options,
  • better patient outcomes and
  • opportunities to analyse rich, heterogeneous datasets from sources: NITRE: Northern Ireland Trusted Research Environment, GPIP: General Practitioner Intelligence Platform, the Honest Broker Service NI and regional deprivation data.

The project will offer the student support from an interdisciplinary team and training to applied advanced AI methods enabling them access to heterogenous data and explore complex interrelationships, and identify patterns and markers that underpin effective diagnosis, intervention and treatment strategies.

This interdisciplinary project connects biology and AI, contributing to next-generation AI methods tailored for complex biomedical challenges. It offers opportunities for the student to deliver significant impact to health outcomes at a population level, advance scientific discovery, receive training in cutting-edge AI and biological science methods, address the challenges posed by diabetes to improve patient outcomes, reduce NHS costs, and address the growing world challenges of diabetes.

Click here to access the application form