Artificial intelligence, data sensors and interconnectivity: future Opportunities for heart failure
Author(s)
Type
Journal Article
Abstract
A higher proportion of patients with heart failure have benefitted from a wide and expanding variety of sensor-enabled implantable devices than any other patient group. These patients can now also take advantage of the ever-increasing availability and affordability of consumer electronics. Wearable, on- and near-body sensor technologies, much like implantable devices, generate massive amounts of data. The connectivity of all these devices has created opportunities for pooling data from multiple sensors - so-called interconnectivity - and for artificial intelligence to provide new diagnostic, triage, risk-stratification and disease management insights for the delivery of better, more personalised and cost-effective healthcare. Artificial intelligence is also bringing important and previously inaccessible insights from our conventional cardiac investigations. The aim of this article is to review the convergence of artificial intelligence, sensor technologies and interconnectivity and the way in which this combination is set to change the care of patients with heart failure.
Date Issued
2020-03-01
Date Acceptance
2020-01-23
Citation
Cardiac Failure Review, 2020, 6, pp.e11-e11
ISSN
2057-7540
Publisher
Radcliffe Cardiology
Start Page
e11
End Page
e11
Journal / Book Title
Cardiac Failure Review
Volume
6
Copyright Statement
© Radcliffe Cardiology 2020. This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/32514380
Subjects
Artificial intelligence
connected care
data sensors
deep learning
heart failure
machine learning
remote monitoring
Publication Status
Published
Coverage Spatial
England