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A team of students and staff from the 1024�˹��� has won first prize in an international computing competition for their work on prototype software to predict a Covid-19 diagnosis. 

The team, from the University’s Centre for Healthcare Modelling and Informatics (CHMI), won the competition organised by Health Data Research UK, beating the likes of Imperial College London and the University of Manchester.

PhD student Connor Price and lecturers Dr Omobolanle Omisade and Elisavet Andrikopoulou took part in the ‘Computable Knowledge Collaborathon’, which aims to explore how a learning health system can use libraries of computable knowledge. 

Connor said: “It was a challenging day tackling data systems and programming language, and we were absolutely thrilled to win first place.  

“Although the purpose of Covid-19 diagnosis prediction has been diminished following the increase in availability of testing, these principles are very transferrable to other diagnoses that could arise in the future.”

The team had to get to grips with FHIR, a healthcare data repository, and Clinical Quality Language, a type of computer programming language, as well as work with GPs and other health professionals to determine a number of factors for diagnosing Covid-19.

Head of the School of Computing, Nick Savage, said: “I am very proud of Elly, Bola and Connor – they were competing against stiff competition from Imperial College London, University College Hospital, NHS Lothian and University Hospital Geneva. It is fantastic they came out on top.” 

The 1024�˹��� team won a £500 donation to the charity of their choice, Diabetes UK.