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Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics. / Kublanov, Vladimir S.; Dolganov, Anton Yu.; Belo, David и др.
в: Applied bionics and biomechanics, 2017.

Результаты исследований: Вклад в журнал › Статья › Рецензирование

Harvard

Kublanov, VS, Dolganov, AY, Belo, D & Gamboa, H 2017, 'Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics', Applied bionics and biomechanics. https://doi.org/10.1155/2017/5985479

APA

Kublanov, V. S., Dolganov, A. Y., Belo, D., & Gamboa, H. (2017). Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics. Applied bionics and biomechanics, [5985479]. https://doi.org/10.1155/2017/5985479

Vancouver

Kublanov VS, Dolganov AY, Belo D, Gamboa H. Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics. Applied bionics and biomechanics. 2017;5985479. doi: 10.1155/2017/5985479

Author

Kublanov, Vladimir S. ; Dolganov, Anton Yu. ; Belo, David и др. / Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics. в: Applied bionics and biomechanics. 2017.

BibTeX

@article{dfc03d393f5a47b19be5b23e88ded353,
title = "Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics",
keywords = "EMPIRICAL MODE DECOMPOSITION, OBSTRUCTIVE SLEEP-APNEA, HEART-RATE-VARIABILITY, ECG, DYNAMICS, SYSTEM, HEALTH",
author = "Kublanov, {Vladimir S.} and Dolganov, {Anton Yu.} and David Belo and Hugo Gamboa",
year = "2017",
doi = "10.1155/2017/5985479",
language = "English",
journal = "Applied bionics and biomechanics",
issn = "1176-2322",
publisher = "Hindawi Publishing Corporation",

}

RIS

TY - JOUR

T1 - Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics

AU - Kublanov, Vladimir S.

AU - Dolganov, Anton Yu.

AU - Belo, David

AU - Gamboa, Hugo

PY - 2017

Y1 - 2017

KW - EMPIRICAL MODE DECOMPOSITION

KW - OBSTRUCTIVE SLEEP-APNEA

KW - HEART-RATE-VARIABILITY

KW - ECG

KW - DYNAMICS

KW - SYSTEM

KW - HEALTH

UR - http://www.scopus.com/inward/record.url?scp=85031328575&partnerID=8YFLogxK

UR - https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=tsmetrics&SrcApp=tsm_test&DestApp=WOS_CPL&DestLinkType=FullRecord&KeyUT=000407088900001

U2 - 10.1155/2017/5985479

DO - 10.1155/2017/5985479

M3 - Article

JO - Applied bionics and biomechanics

JF - Applied bionics and biomechanics

SN - 1176-2322

M1 - 5985479

ER -

ID: 2040012