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Prediction of All-Cause Mortality Following Percutaneous Co..:

Burrello J ; Gallone G ; Burrello A...
info:eu-repo/semantics/altIdentifier/wos/WOS:000815909500001. , 2022

Link: https://hdl.handle.net/11583/2974508

RT Journal
T1 <Title>Prediction of All-Cause Mortality Following Percutaneous Coronary Intervention in Bifurcation Lesions Using Machine Learning Algorithms</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftpoltorinoiris:oai:iris.polito.it:11583_2974508&Exemplar=1&LAN=DE
				
A1 Burrello J
A1 Gallone G
A1 Burrello A
A1 Jahier Pagliari D
A1 Ploumen E. H
A1 Iannaccone M
A1 De Luca L
A1 Zocca P
A1 Patti G
A1 Cerrato E
A1 Wojakowski W
A1 Venuti G
A1 De Filippo O
A1 Mattesini A
A1 Ryan N
A1 Helft G
A1 Muscoli S
A1 Kan J
A1 Sheiban I
A1 Parma R
A1 Trabattoni D
A1 Giammaria M
A1 Truffa A
A1 Piroli F
A1 Imori Y
A1 Cortese B
A1 Omede P
A1 Conrotto F
A1 Chen S. -L
A1 Escaned J
A1 Buiten R. A
A1 Von Birgelen C
A1 Mulatero P
A1 De Ferrari G. M
A1 Monticone S
A1 D'ascenzo F
PB MDPI
YR 2022
K1 coronary bifurcation
K1 machine learning
K1 percutaneous coronary intervention
K1 prognosis
JF info:eu-repo/semantics/altIdentifier/wos/WOS:000815909500001
LK http://dx.doi.org/https://hdl.handle.net/11583/2974508
DO https://hdl.handle.net/11583/2974508
SF ELIB - SuUB Bremen

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