The Secretary of State for Digital, Culture, Media and Sport visited the University today to hear how researchers are being trained to deploy artificial intelligence (AI) in the fight against cancer.
Baroness Nicky Morgan met PhD researchers involved increating the next generation of intelligent technology that will revolutionisehealthcare.
The University is one of 16 centres for doctoral training inAI funded by UKResearch and Innovation, the Government agency responsible forfostering research and development.
The focus of the doctoral training at Leedsis to develop researchers who can apply AIto medical diagnosisand care.
Scientists believe intelligent systems and data analyticswill result in quicker and more accurate diagnosis. Early detection is at theheart of the NHS planto transform cancer survival rates by 2028.
Baroness Morgan said: "Weare committed to being a world leader in artificial intelligence technology andthrough our investment in 16new Centres for Doctoral Training we arehelping train the next generation of researchers.
"It was inspirational to meet some of the leading experts from medicineand computer science working in the new centre at Leeds Universitytoday.They are doing fantastic work to diagnose cancer quicker whichcould save millions of lives."
Baroness Morgan spent time talking to the PhD researchers.
Professor Lisa Roberts, Deputy Vice-Chancellor: Research and Innovation with Baroness Nicky Morgan
Anna Linton is a neuroscientist accepted onto the firstcohort of the programme, which started in the autumn.
She said: The healthcare system can generate a vastquantity of information but sometimes it is assessed in isolation.
I am interested in researching AI systems that can analysemedical notes, the results of pathology tests and scans and identify patternsin that disparate information and make order of it, to give a unified pictureof a patients health status.
That information will help the GP or other healthcareprofessional make a more precise diagnosis.
Dr Emily Clarke is a hospital doctor specialising inhistopathology, the changes in tissue caused by disease. She is an associatemember of the doctoral training programme on a research scholarship from the Medical Research Council.
She wants to develop an AI system to improve the diagnosisof melanoma, a type of skin cancer whose incidence, according to CancerResearch UK, has more than doubled since the early 1990s. It has thefastest rising incidence of any cancer.
Melanoma is detected from the visual examination by ahistopathologist of tissue samples taken during a biopsy. But up to one in sixcases is initially misdiagnosed.
Dr Clarke said: I am hoping we can develop an automatedsystem that can help histopathologists identify melanoma. Diagnosing melanomacan be notoriously difficult so it is hoped that in the future AI may helpbuild a knowledge base of the types of cell changes that are suggestive ofmelanoma and provide a more accurate prediction of a patients prognosis."
Dr Emily Clarke discussing her research project
About 10 researchers will be recruited onto the training programmeeach year. When it is fully up and running, there will be 50 people studyingfor a PhD.
We cant be complacent. We need to ensure there are enough talented and creative people with the skills and knowledge to harness and develop this powerful technology.
Professor Lisa Roberts, Deputy Vice-Chancellor: Researchand Innovation, said: The research at Leeds will ensure the UK remains at theforefront of an important emerging technology that will shape healthcare forfuture generations.
There is little doubt that our researchers will becontribute to future academic and industrial breakthroughs in the field of AI,enabling industry in the UK to remain at the heart of innovation in AI.
David Hogg, Professor of Artificial Intelligence and Director of the Leeds Centre forDoctoral Training, said: The UK is a world leader in AI.
But we cant be complacent. We need to ensure there areenough talented and creative people with the skills and knowledge to harnessand develop this powerful technology.
The PhD researchers will be supervised by leading expertsin computer science and medicine from the University and Leeds TeachingHospitals NHS Trust. To harness thetechnology requires researchers with a strong understanding of medicine,biology and computing and we aim to give that to them.
The researchers joining the Leeds training programme come from a range ofbackgrounds: some are computer scientists and others are biologists orhealthcare professionals but all are able to think computationally and are able to express problems and solutions in a form that can be executed by a computer.
The programme is hosted bythe Leeds Institute for Data Analytics (LIDA), establishedwithUniversityinvestmenttosupport innovation in medical bioinformatics, funded by the MedicalResearch Council, andConsumer Data, funded by the Economic and Social Research Council.
LIDA has now grown to support aportfolio in excess of 45 million of research across the University, bringingtogether over 150 researchers and data scientists. It supports the Universityspartnership withthe Alan Turing Institute, the UKs national institute for data scienceand artificial intelligence.
The University has a strong track record in applyingdigital technologies to healthcare. In partnership with Leeds TeachingHospitals NHS Trust, it is bringing together nine hospitals, seven universitiesand medical technology companies to create a digital pathology network whichwill allow medical staff to collaborate remotely and to conduct AI research. This is known as the Northern Pathology Imaging Co-operative.
Leeds Teaching Hospitals NHS Trust is a leader in usingdigital pathology for cancer diagnosis.
Main photo shows some of the PhD researchers with - front, from left - Professor David Hogg, Director of the Leeds Centre for Doctoral Training, Baroness Nicky Morgan, Secretary of State for Digital, Media, Culture and Sport, and Professor Lisa Roberts, Deputy Vice-Chancellor: Research and Innovation.
See the article here:
Using artificial intelligence to speed up cancer detection - University of Leeds
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