
USFDA
Wikidata: Q204711
ISNI: 0000000122433366
Funder
8 Projects, page 1 of 2
assignment_turned_in Project2019 - 2027Partners:Health Education England, Maudsley Simulation, IMC Business Architecture, HeteroGenius Limited, USFDA +16 partnersHealth Education England,Maudsley Simulation,IMC Business Architecture,HeteroGenius Limited,USFDA,Leeds Teaching Hospitals NHS Trust,One Medical Group,St Gemma's Hospice,TPP,MICROSOFT RESEARCH LIMITED,EPFL,Leeds City Council,Aristotle University of Thessaloniki,Sectra,ASI Data Science (Adv Skills Initiative),Advanced Digital Innovation,NHS England,University of Leeds,FFEI LIMITED,mHabitat,X-Lab LimitedFunder: UK Research and Innovation Project Code: EP/S024336/1Funder Contribution: 5,981,090 GBPArtificial 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.
more_vert Open Access Mandate for Publications assignment_turned_in Project2011 - 2015Partners:LJMU, University of Bradford, ILSI Europe A.I.S.B.L., KNIME, S-IN SOLUZIONI INFORMATICHE SRL +10 partnersLJMU,University of Bradford,ILSI Europe A.I.S.B.L.,KNIME,S-IN SOLUZIONI INFORMATICHE SRL,Insilico Biotechnology (Germany),USFDA,IBBMI,JRC,KI,MolNet,INERIS,MIRA,HENKEL,MERCK KOMMANDITGESELLSCHAFT AUF AKTIENFunder: European Commission Project Code: 266835more_vert assignment_turned_in Project1983 - 1985Partners:USFDAUSFDAFunder: National Science Foundation Project Code: 8304930more_vert assignment_turned_in Project1990 - 1991Partners:USFDAUSFDAFunder: National Science Foundation Project Code: 9021424more_vert assignment_turned_in Project1989 - 1991Partners:USFDAUSFDAFunder: National Science Foundation Project Code: 8910642more_vert
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