Vardas, Panos E;
Asselbergs, Folkert W;
van Smeden, Maarten;
Friedman, Paul;
(2022)
The year in cardiovascular medicine 2021: digital health and innovation.
European Heart Journal
, 43
(4)
pp. 271-279.
10.1093/eurheartj/ehab874.
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Abstract
This article presents some of the most important developments in the field of digital medicine that have appeared over the last 12 months and are related to cardiovascular medicine. The article consists of three main sections, as follows: (i) artificial intelligence-enabled cardiovascular diagnostic tools, techniques, and methodologies, (ii) big data and prognostic models for cardiovascular risk protection, and (iii) wearable devices in cardiovascular risk assessment, cardiovascular disease prevention, diagnosis, and management. To conclude the article, the authors present a brief further prospective on this new domain, highlighting existing gaps that are specifically related to artificial intelligence technologies, such as explainability, cost-effectiveness, and, of course, the importance of proper regulatory oversight for each clinical implementation.
| Type: | Article |
|---|---|
| Title: | The year in cardiovascular medicine 2021: digital health and innovation |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/eurheartj/ehab874 |
| Publisher version: | https://doi.org/10.1093/eurheartj/ehab874 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | AI-ECG, AI-wearables, Big data, Cardiovascular medicine, Digital health, Machine learning |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10160732 |
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