UK – The UK government has announced a hefty £36bn funding boost for artificial intelligence (AI) research technologies in a bid to help the National Health System (NHS) transform the quality of healthcare.
Funding will go toward the winners of the second wave of the NHS AI Lab’s AI in Health and Care Award.
The AI award package also includes funding to support the research, development and testing of early phase, of promising ideas which could be used by the NHS in the future.
Since the first round of the AI in Health and Care Award in September, where £50m was given to 42 AI projects, over 17,000 stroke patients and over 25,000 patients with diabetes have benefited from the new technologies developed.
Health and Social Care Secretary, Matt Hancock said: “AI has the potential to completely revolutionize every part of how we approach healthcare, from how we diagnose diseases and the speed at which our doctors and nurses deliver treatments to how we support people’s mental health.”
“The 38 projects we are backing reflect the UK’s trailblazing approach to innovation in the healthcare sector, and could help us take a leap forward in the quality of care and the speed of disease diagnoses and treatment in the NHS.”
“Confronted with this global pandemic, our tech sector has risen to the challenge and upended how we do things through innovations to support people to test from home, complete remote consultations and diagnose issues safely.”
Currently in the UK, the five big killer diseases that include heart disease, stroke, cancer, lung and liver disease account for more than 150,000 deaths a year among under-75s in England alone and the Department of Health estimates 30,000 of these are entirely avoidable.
Incorporating AI into the NHS will be a gamechanger in reference to making early diagnosis and avoiding such large numbers of fatalities.
The project, AI in Health and Care Award aims to accelerate the testing and evaluation of AI in the NHS so patients can benefit from faster and more personalized diagnosis and greater efficiency in screening services.