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Big Data Institute joins clinical AI network

29/01/19

Mark Say Managing Editor

An Oxford research centre and two hospital trusts have signed deals with healthcare tech company Sensyne Health to explore the use of AI in the sector.

Stethoscope and laptop computer

The Big Data Institute (BDI) is to collaborate with the firm on a project to evaluate the use of clinical AI in understanding chronic diseases, while Wye Valley NHS Trust and George Eliot Hospital NHS Trust have signed strategic research agreements for the analysis of anonymised patient data.

The three-year programme with the BDI will draw on its experience in population health, clinical informatics and machine learning through access to anonymised longitudinal datasets – tracking a specific group over time.

Initially it will focus on chronic kidney disease and cardiovascular disease, with the aim of producing new datasets that capture vital information from patient-clinician consultations. In turn this will make the data available for clinical AI systems to understand the complexities of the diseases.

It could feed into the creation of digital tools and wearables for remote patient monitoring.

In addition, Sensyne and the BDI will aim to develop a pathway to commercialise the work. Under the firm’s business model the commercial value from the research will be shared with any NHS trusts joining the network via a shared equity ownership and shared royalty on revenues.

Improving understanding

Professor Martin Landray, deputy director of the BDI, said: “This new collaboration sets out to improve our understanding of common chronic diseases, identify opportunities for better treatment, and enhance the quality and efficiency of clinical care.”

Both of the hospital trusts will provide longitudinal, anonymised patient data to be analysed by the company’s AI systems.

Sensyne already has strategic research agreements in place with South Warwickshire Hospital, Oxford University Hospitals and Chelsea & Westminster Hospital.

Image by Daniel Sone, public domain via Wikimedia Commons

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