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NHS trusts to deploy AI disease detection platform across 11 hospitals

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A consortium of 10 NHS Trusts is to deploy a new AI-enabled disease detection platform across 11 hospitals.

The AIDE platform is set to be rolled out next year, bringing AI capabilities to clinicians serving some 18 million patients.

The platform is build using the MONAI open-source medical imaging framework co-developed by NVIDIA and the AI Centre.

The framework enables AI applications to interface with hospital systems.

The NHS is will apply the technology in diagnosing and treating conditions ranging from dementia to cancer at Guy’s and St Thomas’s, King’s College Hospital, East Kent Hospital University and University College London Hospitals NHS Foundation Trusts.

James Teo, professor of neurology and data science at King’s College Hospital NHS, said:

“Deployment of this infrastructure for clinical AI tools is a hugely exciting step in integrating AI into healthcare services.

“These platforms will provide a scalable way for clinicians to deploy healthcare AI tools to support decision-making to improve the speed and precision of patient care.

“This is the start of a digital transformation journey with strong, safe and open foundations.”

AI Centre transformation lead, Haris Shuaib, said:

“Across the healthcare ecosystem, researchers, hospitals and startups are realising the power of incorporating a streamlined AI pipeline into their work.

“The open-source MONAI ecosystem is standardising hundreds of AI algorithms for maximum interoperability and impact, enabling their deployment in just a few weeks instead of three-to-six months.”

AI in the NHS

AI is transforming the NHS, with machine learning supporting everything from back-office administration to frontline diagnosis.

A report into the use of AI in the health service was published by Health Education England in February this year.

The report found that diagnostic technology accounted for 34 per cent of the AI used, followed by automation/service efficiency and P4 medicine.

It also revealed that 155 workforce groups across 67 clinical areas were using AI technologies.

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