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Six NHS trusts create partnership to speed up adoption of AI in radiology

The new AI-based radiology platform will enable NHS doctors to make faster diagnoses for heart, cancer and dementia patients

Home / Latest / Six NHS trusts create partnership to speed up adoption of AI in radiology

Six NHS trusts create partnership to speed up adoption of AI in radiology
29th October 2024 about a 3 minute read
“This partnership will enable us to speed up the development of our AI accelerated learning initiatives. We look forward to working more closely together to realise the benefits of AI in clinical practice for patients across the NHS.” Lawrence Tallon, deputy chief executive, Guy’s and St Thomas’ NHS FT

Six NHS trusts have grouped together to adopt a radiology platform based on artificial intelligence (AI).

The partnership, part of a collaboration with the AI Centre for Value Based Healthcare (AI4VBC), is designed to accelerate the NHS’s adoption of radiology AI. The use of AI will, it is hoped, speed up and improve diagnosis and care in a number of care pathways including dementia, heart failure and cancer.

Over the past five years, the AI4VBC, an organisation led by King’s College London and Guy’s and St Thomas’ NHS Foundation Trust, and funded from public sector grants, has developed a number of platforms to provide secure access to electronic health data. This data is then used as the basis for developing AI models and deploying AI technology that can support clinicians and improve the patient experience.

Under the partnership, AI supplier deepc will deploy its deepcOS platform across six NHS trusts, with the aim of expanding to 10 trusts.

The first six trusts to go live with the platform will be Guy’s and St Thomas’ NHS Foundation Trust, King’s College Hospital NHS FT, Lewisham and Greenwich NHS Trust, Imperial College Healthcare NHS Trust, University Hospitals Sussex NHS FT and East Kent Hospitals University NHS FT.

‘Safe and effective’ use of AI

Professor Sebastien Ourselin, director of the AI4VBC said: “Our partnership with deepc will begin by helping six NHS trusts access more than 75 clinically proven AI tools, but that is only the beginning. deepc will play a vital role in supporting the AI4VBC’s future growth.

“Working together, we can make the NHS a true leader in the safe and effective use of AI, ultimately delivering benefits to our patients.”

Lawrence Tallon, deputy chief executive at Guy’s and St Thomas’ NHS FT, said: “This partnership will enable us to speed up the development of our AI accelerated learning initiatives. We look forward to working more closely together to realise the benefits of AI in clinical practice for patients across the NHS.”

Longer term, deepc will work with AI4VBH to build a secure environment where other organisations can develop AI healthcare tools.

Franz Pfister, chief executive and cofounder of deepc, said: “deepc was created to bridge the rapidly growing divide between what the best AI innovations can now achieve within radiology, and health systems’ ability to access those advances.

“Hospitals and doctors know that AI can help them and their patients but they need support to unlock the benefits and navigate the technical and regulatory challenges.

“We’re incredibly proud to announce this long-term strategic collaboration with the AI4VBC to help accelerate and scale the adoption of radiology AI tools within the NHS. Together, we hope to lay the foundations for the NHS to become a true nucleus of excellence for radiology AI globally.”

In March 2024, deepc joined the King’s Health Partners Digital Health Hub to support the development of AI radiology technologies in the UK. In July 2024 it announced that it had closed Series A funding with a €12 million (£10m) extension round, bringing the company’s total funding to date to €30m (£25m).

FCC Insight

Artificial intelligence (AI) has potential to transform diagnosis and treatment. In the field of imaging, a shortage of radiologists has combined with a steep increase in the number of CT and MRI scans to create a worrying backlog. The use of AI to read scans quickly will speed up diagnosis, making sure that patients receive more timely care – which will, in turn, improve outcomes. As a large national health care provider, the NHS is a repository for millions of images and patient records, giving it a significant advantage when it comes to developing AI tools. We are pleased to see collaborations such as the AI4VBC making good use of this resource, helping the NHS to become a pioneer in the adoption of AI while at the same time meeting regulatory compliance requirements.