Antoine Jerusalem, University of Oxford - Electrophysiological-mechanical coupled pulses in neural membranes: a new paradigm for clinical therapy of SCI and TBI (NeuroPulse)
NeuroPulse will build the foundations of a new generation of disruptive and enabling healthcare technologies by exploring and using the interaction between the mechanical vibrational properties of neurons - a specialised cell in the body that transmits nerve impulses - and their electrophysiological functions. This endeavour is set to benefit the medical community in the diagnosis, prognosis, and treatment of TBI and SCI, both major, global public health issues, while providing new avenues for non-invasive electrophysiological control, such as pain management.

David Clifton, University of Oxford - Machine Learning for Patient-Specific, Predictive Healthcare Technologies via Intelligent Electronic Health Records

With an ever-growing quantity of data being acquired during routine care throughout the healthcare system, there is an urgent need to develop integrated, intelligent healthcare technologies that exploit these data to improve patient outcomes. This programme in computational health informatics will develop a machine learning platform for fusing data from electronic health records, patient-worn sensors, and diagnostic data for:

-improved management of patients in hospitals and homes
-better identifying and tracking antibiotic resistance throughout the healthcare system.

Adrien Desjardins, UCL - All-Optical Pulse-Echo Ultrasound Imaging for Real-Time Guidance of Minimally Invasive Procedure
Ultrasound imaging can provide exquisite detail about patient anatomy to guide clinical procedures. Conventionally, ultrasound is transmitted and received electrically. This project is centred on a new paradigm in which ultrasound imaging is performed optically, using inexpensive optical fibres used in telecommunications. The ultrasound probes, developed in close collaboration with clinicians, will be the first to provide real-time optical ultrasound imaging. Integrated into devices such as needles and catheters, they will provide imaging from within the human body that was previously unavailable. There is strong potential to improve patient outcomes in a wide range of clinical contexts.

Silvia Schievano, UCL – A hub for device personalisation in the treatment of congenital diseases - A patient specific computational framework to customise paediatric interventions

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