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COVID-19 is highly contagious, and severe cases can lead to acute failure of the lungs, multiple organs and ultimately death. Chest X-Rays and CT scans provide valuable diagnostic and monitoring information that can complement the laboratory and clinical data. The CMIH is part of a Cambridge led collaboration to bring together clinicians, imaging scientists and AI specialists from Cambridge and throughout the world in support of the fight against COVID-19. The ambitions for the project are to develop a clinical tool for deployment in Addenbrooke's hospital in Cambridge which would help with the future COVID-19 cases. This would then be expanded to other respiratory disease areas in future. In addition, we are keen that AI and data science can be more helpful to future pandemics by developing a blueprint for the things we would have done differently in this pandemic and how we can prepare for the next one.

The team, led by Professors Carola-Bibiane Schönlieb and Evis Sala, brings together expertise in AI for imaging with expertise in radiology and clinical applications from Addenbrooke’s and Royal Papworth Hospitals, as well as collaborators from the UK, China, Austria and Italy, to develop a prediction model that can rapidly and reliably diagnose and suggest a prognosis to doctors.

The collaboration is supported by numerous partners including, DRAGON (a new Innovative Medicines Initiative (IMI) project), Intel, AstraZeneca, and CMIH. Further information on the collaboration, including news and results is available on the AIX-COVNET website.

About Us

The Cambridge Mathematics of Information in Healthcare Hub (CMIH) is a collaboration between mathematics, statistics, computer science and medicine, aiming to develop robust and clinically practical data analytics algorithms for healthcare decision making. Our work focusses on some of the most challenging public health problems; Cancer, Cardiovascular Disease, and Dementia.

 

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