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NHS is using AI but more still needs to be done

Findings from a cloud data firm has revealed that over half of NHS trusts are deploying some sort of AI technology, with a further 16% planning to roll it out in the next two years. Whatsmore, three-quarters of respondents have appointed a leader in AI at their trust.

NetApp announced the findings after requesting the investment in artificial intelligence in the National Health Service (NHS) report from the UK government as part of the Freedom of Information act. 61 trusts responded to the survey which asked recipients about their current and future use of AI, along with how their current data structures are delivering successful artificial related projects.

Where is it being used?

It’s believed that 20% of AI is being used for clinical care and 16% for patient diagnosis. 28% say they use speech recognition, a quarter uses robotic process automation and 13% is using machine learning.

“Artificial intelligence has limitless potential in healthcare services and it’s encouraging to see the technology being used in half of NHS Trusts,” said George Kurian, NetApp chief executive officer and president.

“As healthcare moves towards preventative treatment and personalised medicines, artificial intelligence leaders in the NHS have a complex challenge to break through cultural and organizational barriers when it comes to providing healthcare professionals the access to data they require.”

It’s hoped that using various forms of tech will take the pressure off healthcare workers, accelerate the delivery of personalised medicine and improve overall patient care.

Problems

However, despite the positive outlook of AI stats, there are still many issues the need to be dealt with in order to encourage and improve the use of robotics in the NHS.

It was found that just one-third of respondents had full access to the data required to enable AI deployments. Whilst 39% of Trusts had not invested money into AI projects at all.

Professor Sebastien Ourselin, Head of School of Biomedical Engineering & Imaging Sciences at King’s College London, says: “We are working on end-to-end solutions that embed AI into the clinical pathway, from early diagnostics to therapeutic interventions. High performing and maintainable solutions are key if we are to make these systems trusted and safe for clinical use and NetApp’s findings underline we are moving in the right direction.”

 

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