Artificial intelligence in clinical imaging: a health system approach

F J Gilbert; S W Smye; C-B Schönlieb

doi:10.1016/j.crad.2019.09.122

Artificial intelligence in clinical imaging: a health system approach

Clin Radiol. 2020 Jan;75(1):3-6. doi: 10.1016/j.crad.2019.09.122. Epub 2019 Sep 30.

Authors

F J Gilbert¹, S W Smye², C-B Schönlieb³

Affiliations

¹ Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK. Electronic address: [email protected].
² NIHR Clinical Research Network, School of Population Sciences and Health Services Research, Faculty of Life Sciences & Medicine, Kings College London, 6th Floor, Addison House, Guy's Campus, London SE1 1UL, UK.
³ Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA, UK.

PMID: 31582171
DOI: 10.1016/j.crad.2019.09.122

Abstract

The development and application of artificial intelligence (AI) to radiology requires an approach that encompasses a health system. The UK government and National Health Service (NHS) are creating an ecosystem to facilitate academic/industrial partnerships aimed at accelerating the creation of relevant and robust AI tools, which will improve the development and delivery of healthcare imaging. A series of recent initiatives are described, which will drive the development and adoption of AI in clinical imaging.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Artificial Intelligence*
Diffusion of Innovation
Humans
Radiology / trends*
State Medicine
United Kingdom

Abstract

Publication types

MeSH terms

Grants and funding