Heart Failure diagnosis based on deep learning techniques

The aim of the study is to address the heart failure (HF) diagnosis with the application of deep learning approaches. Seven deep learning architectures are implemented, where stacked Restricted Boltzman Machines (RBMs) and stacked Autoencoders (AEs) are used to pre-train Deep Belief Networks (DBN) a...

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Vydané v:	2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Ročník 2021; s. 1757 - 1760
Hlavní autori:	Papadopoulos, Theofilos G., Plati, Daphni, Tripoliti, Evanthia E., Goletsis, Yorgos, Naka, Katerina K., Rammos, Aidonis, Bechlioulis, Aris, Watson, Chris, McDonald, Kenneth, Ledwidge, Mark, Pharithi, Rebabonye, Gallagher, Joseph, Fotiadis, Dimitrios I.
Médium:	Konferenčný príspevok.. Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.11.2021
Predmet:	Algorithms Biological system modeling Deep Learning Electrocardiography Heart Heart Failure - diagnosis History Hospitals Humans Neural Networks, Computer Sensitivity
ISSN:	2694-0604, 2694-0604
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