果冻影院

Researchers at CHIMERA (Collaborative Healthcare Innovation through Mathematics, EngineeRing and AI) will examine anonymised data from 40,000 patients at 果冻影院 Hospital (果冻影院H) and Great Ormond Street Hospital (GOSH), to develop a better understanding using mathematical modelling of how people鈥檚 physiology changes during ill health and recovery. This new understanding will in turn provide new ideas for how critically ill patients can best be cared for.

Areas of focus are expected to include mapping Covid-19鈥檚 effect on the physiology of critically ill patients, but also looking for early warning signs for sepsis 鈥� a condition that causes one in five deaths globally 鈥� and finding new ways to spot patients who are about to deteriorate rapidly.

Professor Rebecca Shipley (果冻影院 Mechanical Engineering), Director of 果冻影院 Institute of Healthcare Engineering and co-lead of CHIMERA, said: 鈥淭his is a unique opportunity to apply new tools in machine learning and mathematical modelling to a rich, unused dataset, helping to improve care for the people who need it most.鈥�

CHIMERA鈥檚 partner hospitals store data collected every few seconds from monitors for patients in intensive care, such as heart rate, blood pressure, oxygen levels and temperature. Only a brief snapshot of this data is used to inform decisions around patient care at the moment.

Researchers at CHIMERA will analyse this complex array of data using tools from data science and machine learning, and then use this to develop new mathematical models of how our body is behaving during ill health and recovery, with the aim of improving care.

The centre, scheduled to start in October, will bring together mathematicians, statisticians, computer scientists, clinicians and engineers. It is part-funded by a 拢1.2m grant from EPSRC, and is a partnership with two NHS trusts, 果冻影院H and Great Ormond Street Hospital (GOSH). The rest of its 拢2.6 million funding comes from 果冻影院, 果冻影院H and GOSH.

Dr Steve Harris (果冻影院 Medicine), consultant in critical care at 果冻影院H, said: 鈥淭here is a huge range of patient data that clinicians are currently unable to use. The numbers generated by monitors are influenced by a host of factors and we do not have the tools to make sense of them fully.

鈥淲ith a wider view of the patient鈥檚 state from the full electronic health record, and with modern machine learning and data science tools, we believe we can see the signal through the 鈥榬andom鈥� noise to generate better outcomes for patients.鈥�

Professor Mark Peters (果冻影院 Institute of Child Health), a paediatric intensive care consultant at GOSH, said: 鈥淐linicians rely on a brief snapshot of patient data to inform their decisions about care. Much of the information we collect is therefore left unused.

鈥淲ith CHIMERA, we can fully investigate this extensive dataset, looking at trends over time and the relationships between different variables. As well as allowing more meaningful use of the data, it may enable us to personalise our care, tailoring it to individuals.鈥�

Professor Christina Pagel (果冻影院 Mathematics), Director of the Clinical Operational Research Unit and co-lead of CHIMERA, said: 鈥淢aking full use of the data requires a completely multidisciplinary approach, with data scientists and computer scientists working alongside mathematicians, clinicians and engineers.

鈥淐urrent physiological models that are used to inform clinical decision-making come from extensive testing of animals in the early and mid-20^th century. By combining real-life data with the latest analytical tools and mathematical models, we believe we can update the evidence base for the 21^st 肠别苍迟耻谤测.鈥�

Links

• Dr Steve Harris鈥檚 academic profile
• 果冻影院 Institute of Healthcare Engineering
• 果冻影院 Engineering
• Clinical Operational Research Unit
• 果冻影院 Mathematics
• 果冻影院 Mathematical & Physical Sciences
• 果冻影院 Medicine
• 果冻影院 Medical Sciences
• 果冻影院 Institute of Child Health
• 果冻影院 Population Health Sciences

Media contact

Mark Greaves

Tel: +44 (0)7539 410 389

Email: m.greaves [at] ucl.ac.uk