AI in healthcare receives £13m boost from government

UK university and NHS trust projects are to share £13m after winning funding to develop artificial intelligence (AI) for use in healthcare.


Among the winners are University College London (UCL)’s Centre for Interventional and Surgical Sciences, which will use over £500,000 to develop a real-time AI assisted decision support framework to improve surgical outcomes, including avoiding complications following brain tumour surgery and shortening recovery time for patients.

Heriot-Watt University will use £644,000 to develop a system that assists trainee surgeons to practice laparoscopy procedures with real-time feedback on their movements, and Oxford University’s £640,000 will be used to accelerate research into a foundation AI model for clinical risk prediction, an advance that could determine the likelihood of future health problems based on an individual’s existing conditions.

The funding was announced today (August 10, 2023) by technology secretary, Michelle Donelan on a visit to UCL.

“AI will revolutionise the way we live, including our healthcare system,” she said. “That’s why we’re backing the UK’s fantastic innovators to save lives by boosting the frontline of our NHS and tackling the major health challenges of our time.”

In a related development, Matt Clifford, CEO of Entrepreneur First and chair of the Advanced Research and Invention Agency, and Jonathan Black, Heywood Fellow at the Blavatnik School of Government at Oxford University and former UK G7 and G20 Sherpa and deputy National Security Adviser have been appointed to coordinate talks on the safe use of AI ahead of UK summit later this year.

Commenting on today’s announcements, Dr Antonio Espingardeiro, IEEE member, software and robotics specialist, said “In recent years, we have seen AI become a credible part of our healthcare ecosystem. As it becomes more sophisticated, AI can efficiently conduct tasks traditionally undertaken by humans, the potential for the technology within the medical field is huge. It can analyse vast quantities of information, and when coupled with machine learning, search through records and infer patterns or anomalies in data, that would otherwise take decades for humans to analyse.”

Ayesha Iqbal, IEEE senior member and engineering trainer at the MTC’s advanced manufacturing training centre, added: “Despite numerous applications being considered promising, the adoption of AI in healthcare is facing some challenges, such as complexity of AI systems, lack of technology awareness, lack of skilled AI workforce and regulatory guidelines, and lack of trust.

“Therefore, it is crucial to establish ethical guidelines and standards, ensure data privacy and security, offer trialability, and educate patients so that trust can be developed. At that point, widespread adoption of AI in healthcare can be realised."