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. The project will define new near miss and severe morbidity definitions allowing us to identify electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset
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electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset for the first time. This will allow us to work out the best vital-sign-based early warning score
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techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both keyword-based search and SPARQL querying. EPRESSO will build on and
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to modern slavery in conflict settings. This attempt requires a large, interdisciplinary team working within a cross-cutting framework to connect vast amounts of data and answer many fundamental questions
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apply the Helsinki Discrete Element Model (HiDEM) to simulations of brittle-elastic fracture, calving and retreat at Kangerlussuaq Gletsjer (KG), a large outlet glacier of the Greenland Ice Sheet. Working
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clinical trial portfolio for a research programme in antimicrobial resistance and work to support colleagues in data-enabled trials. You will also undertake statistical methods research associated with
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business, Improving health & public services organisation, Strengthening economic & financial systems as well as our overarching themes AI, Digitalisation, Big data and Automation. King's expects all
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digital infrastructure and transport infrastructure, and the need to provide standard services, including emergency responses, across large geographical areas. The aims of the CARMHRS study are: To improve
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observation tasks, health economics data and a large battery of questionnaires. Because of the quality of the datasets, the elevated risk of children involved and the importance of the research questions, we
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will develop, implement, and apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics