Owkin, NVIDIA team up to deliver AI to hospitals

by | 2nd Dec 2019 | News

The project puts an emphasis on the integrity and security of patient data, an important topic at the moment.

Owkin has announced a new partnership with NVIDIA and King’s College London (KCL), in order to deliver the company’s “Federated Learning” software in the healthcare and life sciences sector.

The US-based company, which is developing Federated Learning and AI technologies to advance medical research, explained that the project will initially connect four of London’s premier teaching hospitals before expanding throughout the UK, and will offer AI services to accelerate research and improve clinical practice in a wide range of therapeutic areas, including cancer, heart failure and neurodegenerative disease.

Further, KCL will use Owkin’s Federated Learning software and NVIDIA’s EGX Intelligent Edge Computing platform to develop research, clinical and operational improvements across a large number of clinical pathways, such as the above mentioned.

The project puts an emphasis on the integrity and security of patient data, an important topic at the moment. The news comes shortly after a new survey revealed that that the mass majority of NHS staff are not comfortable with the idea of “big tech” companies analysing their patient data. Just 12% of healthcare professionals in the poll felt comfortable with the companies analysing their anonymised patient data, despite 81% thinking that general analysis of such data would help enable quicker diagnosis and more effective treatment.

The ultimate aim is to “build a community of academic and private sector researchers that can collaborate to use advanced imaging and AI to develop insight as well as clinical and operational tools that will substantially improve the experience and the clinical outcomes of our patients.”

Sebastien Ourselin, Professor of Healthcare Engineering at KCL went on to say that KCL is “very pleased to welcome Owkin into our consortium of partners”, and that it will enable them to “learn from data at scale, while preserving patient privacy.”

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