Towards nationally curated data archives for clinical radiology image analysis at scale: Learnings from national data collection in response to a pandemic

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Cushnan, Dominic, Berka, Rosalind, Bertolli, Ottavia, Williams, Peter, Schofield, Daniel, Joshi, Indra, Favaro, Alberto, Halling-Brown, Mark, Imreh, Gergely, Jefferson, Emily et al (show 24 more authors) , Sebire, Neil J, Reilly, Gerry, Rodrigues, Jonathan CL, Robinson, Graham, Copley, Susan, Malik, Rizwan, Bloomfield, Claire, Gleeson, Fergus, Crotty, Moira, Denton, Erika, Dickson, Jeanette, Leeming, Gary ORCID: 0000-0002-5554-5302, Hardwick, Hayley E, Baillie, Kenneth, Openshaw, Peter JM, Semple, Malcolm G ORCID: 0000-0001-9700-0418, Rubin, Caroline, Howlett, Andy, Rockall, Andrea G, Bhayat, Ayub, Fascia, Daniel, Sudlow, Cathie, Jacob, Joseph and Collaborative, NCCID (2021) Towards nationally curated data archives for clinical radiology image analysis at scale: Learnings from national data collection in response to a pandemic. DIGITAL HEALTH, 7. 20552076211048654-. ISSN 2055-2076, 2055-2076

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Abstract

The prevalence of the coronavirus SARS-CoV-2 disease has resulted in the unprecedented collection of health data to support research. Historically, coordinating the collation of such datasets on a national scale has been challenging to execute for several reasons, including issues with data privacy, the lack of data reporting standards, interoperable technologies, and distribution methods. The coronavirus SARS-CoV-2 disease pandemic has highlighted the importance of collaboration between government bodies, healthcare institutions, academic researchers and commercial companies in overcoming these issues during times of urgency. The National COVID-19 Chest Imaging Database, led by NHSX, British Society of Thoracic Imaging, Royal Surrey NHS Foundation Trust and Faculty, is an example of such a national initiative. Here, we summarise the experiences and challenges of setting up the National COVID-19 Chest Imaging Database, and the implications for future ambitions of national data curation in medical imaging to advance the safe adoption of artificial intelligence in healthcare.

Item Type:	Article
Uncontrolled Keywords:	Imaging, medicine, radiology, respiratory, machine learning, general, artificial intelligence, coronavirus SARS-CoV-2 disease
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Population Health
Depositing User:	Symplectic Admin
Date Deposited:	13 Dec 2021 08:15
Last Modified:	06 Dec 2024 20:11
DOI:	10.1177/20552076211048654
Open Access URL:	https://journals.sagepub.com/doi/10.1177/205520762...
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3145176