TY - JOUR
T1 - The year in cardiovascular medicine 2021
T2 - digital health and innovation
AU - Friedman, Paul
AU - Vardas, Panos E.
AU - Asselbergs, Folkert W.
AU - van Smeden, Maarten
N1 - Funding Information:
The authors thank the following for their contributions to the preparation of the manuscript: Dr Anastasia Xintarakou, Mr Philip Lees, and Ms Alexandra Kourlampa. Thanks also to Professors E. Peyster and S. Khurshid for permission to use the figures.
Publisher Copyright:
© The Author(s) 2022.
PY - 2022/1/21
Y1 - 2022/1/21
N2 - 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.
AB - 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.
KW - AI-ECG
KW - AI-wearables
KW - Big data
KW - Cardiovascular medicine
KW - Digital health
KW - Machine learning
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U2 - 10.1093/eurheartj/ehab874
DO - 10.1093/eurheartj/ehab874
M3 - Article
C2 - 34974610
AN - SCOPUS:85123969113
SN - 0195-668X
VL - 43
SP - 271
EP - 279
JO - European Heart Journal
JF - European Heart Journal
IS - 4
ER -