Aiming to simplify and speed up complicated radiology workflows,
NVIDIA and King’s College London today announced they are
partnering to build an AI platform that will in the near future
allow specialists in the U.K.’s National Health Service (NHS) to
train computers to automate the most time-consuming part of
radiology interpretation.
The collaboration is part of King’s London Medical Imaging &
AI Centre for Value-Based Healthcare, an ongoing project intended
to transform 12 clinical pathways in oncology, cardiology and
neurology, as well as improve diagnoses and patient care in the
NHS.
The work could lead to breakthroughs in classifying stroke and
neurological impairments, determining the underlying causes of
cancers and recommending the best treatments for patients.
NVIDIA DGX-2 AI Systems Power First Point-of-Care
PlatformKing’s is implementing NVIDIA®️ DGX-2™ systems,
which are 2-petaflops GPU-powered supercomputers for AI research,
as part of the first phase of the project. It will also use the
NVIDIA Clara AI toolkit with its own imaging technologies, for
example NiftyNet, as well as those from partners such as Siemens,
Kheiron Medical, Mirada and Scan.
The NVIDIA Clara AI toolkit is a key part of the NVIDIA Clara
developer platform, on which intelligent workflows can be built.
NVIDIA Clara consists of libraries for data and image processing,
AI model processing, and visualization.
Researchers and engineers from NVIDIA and King’s will also join
clinicians from major London hospitals onsite at King’s College
Hospital, Guy’s and St Thomas’, and South London and Maudsley. This
combination of research, technology and clinicians will accelerate
the discovery of data strategies, resolve targeted AI problems and
speed up deployment in clinics.
Federated Learning Supports Data PrivacyFor the
first time in the NHS, federated learning will be applied to
algorithm development, ensuring the privacy of patient data.
Federated learning allows AI algorithms to be developed at multiple
sites, using data from each individual hospital, without the need
for data to travel outside of its own domain.
This approach is crucial for the development of AI in clinical
environments, where the security and governance of data is of the
highest importance. AI models will be developed in different NHS
trusts across the U.K., built on data from different patient
demographics and clinical attributes.
With models developed at individual NHS trusts, the data will
give more accurate and representative insight into patients from
that particular area. The NHS will also be able to combine these
trust-specific models to build a larger, demographically richer
overall model.
By bringing together a critical mass of industry and university
partners, the London Medical Imaging & AI Centre for
Value-Based Healthcare will allow the NHS to share and analyze data
on a scale that has not previously been possible, according to
Professor Sebastien Ourselin, head of the School of Biomedical
Engineering & Imaging Sciences at King’s College London.
“This centre marks a significant chapter in the future of
AI-enabled NHS hospitals, and the infrastructure is an essential
part of building new AI tools which will benefit patients and the
healthcare system as a whole,” said Professor Ourselin. “The NVIDIA
DGX-2 AI system’s large memory and massive computing power make it
possible for us to tackle training of large, 3D datasets in minutes
instead of days while keeping the data secure on the premises of
the hospital.”
Jaap Zuiderveld, vice president for EMEA at NVIDIA, said,
“Together with King’s College London, we’re working to push the
envelope in AI for healthcare. DGX-2 systems with the NVIDIA Clara
platform will enable the project to scale and drive breakthroughs
in radiology ultimately help improve patient outcomes within the
NHS.”
The collaboration between NVIDIA and King’s College London is
part of the UKRI program for Radiology and Pathology, an innovation
fund that has supported the growing community looking to integrate
AI workflows into the NHS.
About NVIDIA NVIDIA‘s (NASDAQ: NVDA) invention
of the GPU in 1999 sparked the growth of the PC gaming market,
redefined modern computer graphics and revolutionized parallel
computing. More recently, GPU deep learning ignited modern AI — the
next era of computing — with the GPU acting as the brain of
computers, robots and self-driving cars that can perceive and
understand the world. More information at
http://nvidianews.nvidia.com/.
For further information, contact:Kasia
JohnstonSenior PR Manager for Healthcare and IndustriesNVIDIA
Corporationkasiaj@nvidia.com
Jens NeuschaeferPR Manager Industry EMEANVIDIA
Corporation+49-89-6283-50015jneuschaefer@nvidia.com
Certain statements in this press release including, but not
limited to, statements as to: NVIDIA and King’s College London
building the U.K.’s first AI platform for NHS hospitals; the
benefits, impacts, performance and abilities of NVIDIA DGX-2, the
AI systems it powers and the NVIDIA Clara AI toolkit; the AI
platform allowing specialists in the NHS to train computers to
automate the most time-consuming part of radiology interpretation;
the benefits and impact of NVIDIA and King’s College London’s
collaboration, including the medical breakthroughs it could
facilitate, the data giving more accurate and better insight into
patients, and the use of trust-specific models to build larger
demographically richer overall models; King’s College London’s
projects intention to transform clinical pathways, improve
diagnoses and patient care; the collaboration joining clinicians
for various hospitals and its ability to accelerate the discovery
of data strategies, resolve targeted AI problems and speed up
deployment in clinics; the benefits and impacts of federated
learning being applied to algorithm development; the London Medical
Imaging & AI Centre for Value-Based Healthcare allowing the NHS
to share and analyze data on a scale that has not previously been
possible, it marking a significant chapter in the future of
AI-enabled NHS hospitals, and it being an essential part of
building new AI tools that will benefit patients and the healthcare
system as a whole; NVIDIA DGX-2 AI system making it possible to
train large datasets in minutes, instead of days while keeping the
data secure; and DGX-2 systems and NVIDIA Clara enabling the
collaboration with King’s College London to scale and drive
breakthroughs in radiology and help improve patient outcomes are
forward-looking statements that are subject to risks and
uncertainties that could cause results to be materially different
than expectations. Important factors that could cause actual
results to differ materially include: global economic conditions;
our reliance on third parties to manufacture, assemble, package and
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enhancements to our existing product and technologies; market
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