AI Funding to Speed up Disease Diagnosis
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A £50 million funding boost for the UK’s NHS will scale up the work of existing Digital Pathology and Imaging Artificial Intelligence Centres of Excellence, which were launched in 2018 to develop cutting-edge digital tools to improve the diagnosis of disease. The three centres set to receive a share of the funding, based in Coventry, Leeds and London, will deliver digital upgrades to pathology and imaging services across an additional 38 NHS trusts, benefiting 26.5 million patients across England.
Pathology and imaging services, including radiology, play a crucial role in the diagnosis of diseases and the funding will lead to faster and more accurate diagnosis and more personalised treatments for patients, freeing up clinicians’ time and ultimately saving lives.
The new funding is part of the government’s commitment to saving thousands more lives each year and detecting three-quarters of all cancers at an early stage by 2028. Cancer diagnosis and treatment has been an absolute priority throughout the pandemic and continues to be so.
National Pathology Imaging Co-operative Director and Consultant Pathologist at Leeds Teaching Hospitals NHS Trust Darren Treanor said: “This investment will allow us to use digital pathology to diagnose cancer at 21 NHS trusts in the north, serving a population of 6 million people. We will also build a national network spanning another 25 hospitals in England, allowing doctors to get expert second opinions in rare cancers, such as childhood tumours, more rapidly. This funding puts the NHS in a strong position to be a global leader in the use of artificial intelligence in the diagnosis of disease.”
Professor Reza Razavi, London Medical Imaging and AI Centre for Value-Based Healthcare Director, commented: “Artificial intelligence technology provides significant opportunities to improve diagnostics and therapies as well as reduce administrative costs. With machine learning, we can use existing data to help clinicians better predict when disease will occur, diagnosing and treating it earlier, and personalising treatments, which will be less resource intensive and provides better health outcomes for our patients.”
