Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data
AU - Khamzin, Svyatoslav
AU - Dokuchaev, Arsenii
AU - Bazhutina, Anastasia
AU - Chumarnaya, Tatiana
AU - Zubarev, Stepan
AU - Lyubimtseva, Tamara
AU - Lebedeva, Viktoria
AU - Lebedev, Dmitry
AU - Gurev, Viatcheslav
AU - Solovyova, Olga
N1 - Publisher Copyright: Copyright © 2021 Khamzin, Dokuchaev, Bazhutina, Chumarnaya, Zubarev, Lyubimtseva, Lebedeva, Lebedev, Gurev and Solovyova.
PY - 2021/12/14
Y1 - 2021/12/14
KW - cardiac modeling
KW - cardiac resynchronization therapy
KW - electrophysiology
KW - heart failure
KW - hybrid approach
KW - machine learning
KW - prediction
KW - EXCITATION
KW - CRT
KW - DYSSYNCHRONY
KW - HEART
KW - INTELLIGENCE
KW - RESYNCHRONIZATION THERAPY
KW - ELECTROPHYSIOLOGY
KW - VENTRICULAR LEAD IMPLANTATION
KW - MAGNETIC-RESONANCE
KW - DEFIBRILLATOR
UR - http://www.scopus.com/inward/record.url?scp=85121850404&partnerID=8YFLogxK
UR - https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=tsmetrics&SrcApp=tsm_test&DestApp=WOS_CPL&DestLinkType=FullRecord&KeyUT=000737529300001
UR - https://elibrary.ru/item.asp?id=47549916
U2 - 10.3389/fphys.2021.753282
DO - 10.3389/fphys.2021.753282
M3 - Article
AN - SCOPUS:85121850404
VL - 12
JO - Frontiers in Physiology
JF - Frontiers in Physiology
SN - 1664-042X
M1 - 753282
ER -
ID: 29207012