A partnership between King’s Collect London (KCL), chipmaker NVIDIA and artificial intelligence (AI) developer Owkin will see the launch of a vast AI network across hospital sites in the UK.
Dubbed the King’s College London Medical Imaging and AI Centre for Value Based Healthcare (AI4VBH), it will see an AI network initially connecting four of the leading research hospitals in London, as well as three universities, before being rolled out to 12 other hospitals in the UK.
It will use anonymised patient data across the network, connected using a blockchain-based system, to identify areas that clinical practice can be improved, as well identify routes to advance research in a host of key therapeutic areas, including neurodegenerative disease, cardiovascular conditions and cancer.
“This partnership brings together the best players in life science & healthcare, machine learning and data center infrastructure,” said Gilles Wainrib, co-founder and chief scientific officer of Owkin, which specialises in AI for medical settings, including hospital environments.
“NVIDIA’s platforms create the ideal and flexible footprint for hospitals to invest in machine learning. King’s College London has assembled the engineering, medical and data science talent, the high-quality patient data and the governance framework in the AI4VBH Centre that will show the world the future of healthcare analytics and the power of machine learning.
“Together we will be enabling the formation of a decentralised dataset that will generate enormous value for research and clinical practice.”
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Using federated learning to fuel hospital AI
The network uses a machine learning system known as federated learning, where the AI network is spread across large numbers of different systems. This removes the need for high-powered machines.
“Owkin hopes to demonstrate that a Federating Learning architecture is safer for patients, and statistically equivalent to the traditional pooled model for analysis,” said Wainrib.
“Owkin also sees huge research potential to analyse the patient data in the AI4VBH Centre to identify new biomarkers and high value subgroups for clinical trial design and diagnostics.”
The technology is designed to ensure high levels of patient privacy – a particularly important feature in AI designed for use in hospital environments.
“Owkin has developed a highly flexible, secure, traceable and privacy-preserving software stack that brings federated learning to life. It allows data scientists to design federated learning strategies and it orchestrates the travel of algorithms from one hospital to another,” added Craig Rhodes, EMEA Industry Lead for Artificial Intelligence Healthcare and Life Science at NVIDIA.
“Importantly for the European context, where GDPR is a requirement, Owkin’s blockchain-based traceability platform gives hospital information governors the assurance they need that a patient’s data is being respected and protected.”
“Owkin are thought leaders in the new field of federated learning, and will make an important contribution to the AI Centre by providing the software layer that allows models to be built, orchestrated, secured and traced as they travel between our hospital and university partners,” added Sebastien Ourselin, Professor of Healthcare Engineering at KCL.
“This is enables us to learn from data at scale, while preserving patient privacy. It also ensures that the predictive models developed from patient data are representative and unbiased because they will be trained on the widest possible population of patient data, which in phase 1 includes one third of the London population and will extend far beyond London in coming years.
“We truly see this architecture as the future of healthcare informatics.”