Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Nov 23:7:20552076211048654.
doi: 10.1177/20552076211048654. eCollection 2021 Jan-Dec.

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

Affiliations

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

Dominic Cushnan et al. Digit Health. .

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.

Keywords: Imaging; artificial intelligence; coronavirus SARS-CoV-2 disease; general; machine learning; medicine; radiology; respiratory.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
National COVID-19 Chest Imaging Database (NCCID) infrastructure and explanation.

References

    1. Ker J, Wang L, Jai Ret al. et al. Deep learning applications In medical image analysis. IEEE Access 2017; 6: 9375–9389.
    1. Jin C, Chen W, Cao Yet al. Development and evaluation of an artificial intelligence system for COVID-19 diagnosis. Nat Commun 2020; 11: 1–14. - PMC - PubMed
    1. Wehbe RM, Sheng J, Dutta Set al. DeepCOVID-XR: an artificial intelligence algorithm to detect COVID-19 on chest radiographs trained and tested on a large US clinical data set. Radiology 2021 Apr; 299: E167–E176. - PMC - PubMed
    1. Feng Z, Yu Q, Yao Set al. Early prediction of disease progression In COVID-19 pneumonia patients with chest CT and clinical characteristics. Nat Commun 2020; 11: 1–9. - PMC - PubMed
    1. Shamout FE., Shen Y., Wu N., et al. 2021. An artificial intelligence system for predicting the deterioration of COVID-19 patients In the emergency department. NPJ digital medicine, 4, pp.1–11. - PMC - PubMed

LinkOut - more resources