The use of the latest Artificial Intelligence will benefit patients in the UK with faster treatment, better outcomes, and shorter hospital stays.
Over 40,000 CT scans, MRIs, and x-rays from more than 10,000 patients have been brought together by NHSX throughout the pandemic to create a National COVID-19 Chest Imaging Database (NCCID). Hospitals and universities across the country are using the database to track patterns and markers of COVID-19 in patients, to quickly create treatment plans, and to better understand whether a patient will end up in a critical condition.
The NCCID is also helping researchers from universities in University College London, and in Bradford, to develop AI tools that could help doctors improve the treatment for patients with COVID-19.
Predictive, preventive, and personalised health
Clinicians at Addenbrooke’s Hospital in Cambridge are developing an algorithm based on the NCCID database that will help to inform a more accurate diagnosis of patients when they present with potential COVID-19 symptoms without a positive test. This will help clinicians to implement earlier medical interventions, including giving patients oxygen and medication before reaching a critical stage of the illness.
The database can also help clinicians predict the need for additional ICU capacity, enabling the management of beds and staff resource in those settings.
Matt Hancock, Secretary of State for Health and Social Care, said: “The use of artificial intelligence is already beginning to transform patient care by making the NHS a more predictive, preventive, and personalised health and care service. It is vital we always search for new ways to improve care, especially as we fight the pandemic with the recovery beyond. This excellent work is testament to how technology can help to save lives in the UK.”
Carola-Bibiane Schönlieb, Professor of Applied Mathematics and head of the Cambridge Image Analysis group at the University of Cambridge, said: “The NCCID has been invaluable in accelerating our research and provided us with a diverse, well-curated, dataset of UK patients to use in our algorithm development. The ability to access the data for 18 different trusts centrally has increased our efficiency and ensures we can focus most of our time on designing and implementing the algorithms for use in the clinic for the benefit of patients.
“By understanding in the early stages of disease whether a patient is likely to deteriorate we can intervene earlier to change the course of their disease and potentially save lives as a result.”
The database is also helping with the development of a national AI imaging platform that will allow for the safe collecting and sharing of data, developing AI technologies to address a number of other conditions such as heart disease and cancers.
