TinyML and edge intelligence applications in cardiovascular disease: A survey

Tiny machine learning (TinyML) and edge intelligence have emerged as pivotal paradigms for enabling machine learning on resource-constrained devices situated at the extreme edge of networks. In this paper, we explore the transformative potential of TinyML in facilitating pervasive, low-power cardiov...

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Bibliographic Details
Published in:	Computers in biology and medicine Vol. 186; p. 109653
Main Authors:	Keivanimehr, Ali Reza, Akbari, Mohammad
Format:	Journal Article
Language:	English
Published:	United States Elsevier Ltd 01.03.2025 Elsevier Limited
Subjects:	Algorithms Artificial intelligence Artificial neural networks Belief networks Cardiovascular disease Cardiovascular diseases Cardiovascular Diseases - diagnosis Cardiovascular Diseases - physiopathology Cloud computing Constraints Deep learning Deep neural networks Edge intelligence EKG Electrocardiography Energy consumption Health care industry Heart Humans Intelligence Internal Medicine Internet of Things Learning algorithms Machine Learning Monitoring Neural networks Neural Networks, Computer Other Power management Privacy Real time Software Telemedicine TinyML Wearable computers Wearable Electronic Devices Wearable technology Wide area networks Internet of things Deep neural networks Cardiovascular diseases TinyML Edge intelligence
ISSN:	0010-4825, 1879-0534, 1879-0534
Online Access:	Get full text
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