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Details of Grant 

EPSRC Reference: EP/S024336/1
Title: UKRI Centre for Doctoral Training in Artificial Intelligence for Medical Diagnosis and Care
Principal Investigator: Hogg, Professor D
Other Investigators:
Hall, Professor G Johnson, Mr OA Velikova, Professor G
Treanor, Dr D Dimitrova, Prof. V
Researcher Co-Investigators:
Project Partners:
Advanced Digital Innovation Aristotle University of Thessaloniki ASI Data Science (Adv Skills Initiative)
FFEI Limited Health Education England HeteroGenius Limited
IMC Business Architecture Leeds City Council Leeds Teaching Hospitals NHS Trust
Maudsley Simulation mHabitat Microsoft
NHS England One Medical Group Sectra
St Gemma's Hospice Swiss Federal Inst of Technology (EPFL) TPP
US Food and Drug Administration X-Lab Limited
Department: Sch of Computing
Organisation: University of Leeds
Scheme: Centre for Doctoral Training
Starts: 01 April 2019 Ends: 30 September 2027 Value (£): 6,212,167
EPSRC Research Topic Classifications:
Artificial Intelligence
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
07 Nov 2018 UKRI Centres for Doctoral Training AI Interview Panel V – November 2018 Announced
Summary on Grant Application Form
Artificial Intelligence (AI) has advanced rapidly over the last five years, largely as a result of new algorithms, affordable hardware, and huge increases in the availability of data in digital form.

The UK has recognised as a national priority the urgent need to exploit AI in human health, where digital data is being created from many sources, for example: images from tissue slices, X-ray devices, and ultrasound; along with laboratory tests, genetic profiles, and the health records used by GPs and hospitals.

The potential is enormous. In future, AI could automatically identify those at risk of cancer before symptoms appear, suggesting changes in lifestyle that would reduce long-term risk. It could greatly speed-up and increase the reliability of diagnostic services such as pathology and radiology. It could help doctors and patients select the most appropriate care pathway based on personal history and clinical need.

Such improvements will lead to better care and more cost-effective use of resources in the NHS.

Our Centre for Doctoral Training will train the future researchers who will lead on this transformation. They will come from a variety of backgrounds in science, engineering and health disciplines. When they graduate from the Centre after four years, they will have the AI knowledge and skills, coupled with real-world experience in the health sector, to unlock the immense potential of AI within the health domain.

Our scope is on AI for medical diagnosis and care with a focus on cancer for which there are particularly rich sources of digital data, and where AI is expected to lead to significant breakthroughs. Leading with cancer, we will inform the use of AI in medical diagnosis and care more widely.

The Centre will be based in the City of Leeds, which has developed into the home of the NHS in England. The University of Leeds and the Leeds Teaching Hospitals Trust (LTHT), working with key national partners from the NHS and industry, provides the ideal environment for this Centre. There is internationally excellent research on AI and on cancer, including a world leading centre for digital pathology. There is already strong collaboration between the different organisations involved.

The Centre builds on a well-established track record in transferring research ideas into world-leading clinical practice and new products. Our graduates will become international leaders in academia and industry, ensuring the UK remains at the forefront in health research, clinical practice and commercial innovation.

Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.leeds.ac.uk