| EPSRC Reference: |
EP/T017791/1 |
| Title: |
CHIMERA: Collaborative Healthcare Innovation through Mathematics, EngineeRing and AI |
| Principal Investigator: |
Shipley, Professor RJ |
| Other Investigators: |
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| Department: |
Mechanical Engineering |
| Organisation: |
UCL |
| Scheme: |
Standard Research |
| Starts: |
01 November 2020 |
Ends: |
31 October 2024 |
Value (£): |
1,059,447
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Mathematical Analysis |
| Med.Instrument.Device& Equip. |
Statistics & Appl. Probability |
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Summary on Grant Application Form |
Hospitals collect a wealth of physiological data that provide information on patient health. Full use of this data is significantly limited by its complexity and by a limited mechanistic understanding of the relationship between internal physiology and external measurement. Addressing this challenge requires multidisciplinary collaboration between mathematicians developing new biomechanical models, clinicians who measure and interpret the data to treat patients, and statistical and computational scientists to bridge the two-way translation between model output and real-life data. CHIMERA is designed to foster such collaboration to generate new understanding of physiology, new methods for relating physiology to real time data, and, finally, to translate these into practice, improving outcomes for patients by supporting clinical decision making.
CHIMERA will start by focusing on the most critically ill patients within hospital intensive care units: such patients have by far the most monitoring data and are most likely to benefit from improved understanding of what that data can tell us about their underlying physical state. Each year about 20,000 children and 300,000 adults in the UK need intensive care. These critically ill patients are continuously monitored at the bedside, including measurements of heart rate, breathing rate, blood pressure and other vital sign data. However, the wealth of these physiological data are not currently used to inform clinical decision making and clinicians can only really use real-time snapshots of the physiology to guide their decisions.
CHIMERA will address this unmet opportunity to use individual patient physiological data to support clinical decision making, with the potential to impact on patient management across the UK and beyond. This will be achieved through a multidisciplinary Hub which brings together experts in mathematics, statistics, data science and machine learning, with unique, high volume and rich data sets from both adult and paediatric Intensive Care Units provided through embedded Project Partnerships with Great Ormond Street Hospital (GOSH) and University College London Hospital (UCLH). CHIMERA will deliver new mathematical frameworks to learn the biophysical relationships that govern the interdependencies between physiological variables, based on data sets for thousands of patients through these project partners. Clinical impact will be achieved through an extensive series of clinically-led, multidisciplinary workshops themed around specific opportunities to improve care, for example identifying deteriorating patients in advance of an adverse event such as heart attack or stroke, or advance warning systems to diagnose sepsis. These workshops will include partnering with the Alan Turing Institute (the national centre for AI and Data Science), will be open to national participation, and will provide a mechanism to fund new projects by making available seed corn funding, PhD studentships and researcher resource for new interdisciplinary teams and partnerships. CHIMERA will build new links with clinical centres, companies and academic units across the UK and internationally, expand to work with a variety of patient monitoring data, and provide dedicated support to nurture new projects, funding bids and collaborations. In this way, we will build CHIMERA to a self-sustaining, multidisciplinary and vibrant Centre for the application of mathematical and data sciences tools in patient care.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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