Improving 1-year mortality prediction in ACS patients using machine learning

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Standard

Improving 1-year mortality prediction in ACS patients using machine learning. / Weichwald, Sebastian; Candreva, Alessandro; Burkholz, Rebekka; Klingenberg, Roland; Räber, Lorenz; Heg, Dik; Manka, Robert; Gencer, Baris; Mach, François; Nanchen, David; Rodondi, Nicolas; Windecker, Stephan; Laaksonen, Reijo; Hazen, Stanley L; Von Eckardstein, Arnold; Ruschitzka, Frank; Lüscher, Thomas F; Buhmann, Joachim M; Matter, Christian M.

I: European Heart Journal: Acute Cardiovascular Care, Bind 10, Nr. 8, 2021, s. 855-865.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Weichwald, S, Candreva, A, Burkholz, R, Klingenberg, R, Räber, L, Heg, D, Manka, R, Gencer, B, Mach, F, Nanchen, D, Rodondi, N, Windecker, S, Laaksonen, R, Hazen, SL, Von Eckardstein, A, Ruschitzka, F, Lüscher, TF, Buhmann, JM & Matter, CM 2021, 'Improving 1-year mortality prediction in ACS patients using machine learning', European Heart Journal: Acute Cardiovascular Care, bind 10, nr. 8, s. 855-865. https://doi.org/10.1093/ehjacc/zuab030

APA

Weichwald, S., Candreva, A., Burkholz, R., Klingenberg, R., Räber, L., Heg, D., Manka, R., Gencer, B., Mach, F., Nanchen, D., Rodondi, N., Windecker, S., Laaksonen, R., Hazen, S. L., Von Eckardstein, A., Ruschitzka, F., Lüscher, T. F., Buhmann, J. M., & Matter, C. M. (2021). Improving 1-year mortality prediction in ACS patients using machine learning. European Heart Journal: Acute Cardiovascular Care, 10(8), 855-865. https://doi.org/10.1093/ehjacc/zuab030

Vancouver

Weichwald S, Candreva A, Burkholz R, Klingenberg R, Räber L, Heg D o.a. Improving 1-year mortality prediction in ACS patients using machine learning. European Heart Journal: Acute Cardiovascular Care. 2021;10(8):855-865. https://doi.org/10.1093/ehjacc/zuab030

Author

Weichwald, Sebastian ; Candreva, Alessandro ; Burkholz, Rebekka ; Klingenberg, Roland ; Räber, Lorenz ; Heg, Dik ; Manka, Robert ; Gencer, Baris ; Mach, François ; Nanchen, David ; Rodondi, Nicolas ; Windecker, Stephan ; Laaksonen, Reijo ; Hazen, Stanley L ; Von Eckardstein, Arnold ; Ruschitzka, Frank ; Lüscher, Thomas F ; Buhmann, Joachim M ; Matter, Christian M. / Improving 1-year mortality prediction in ACS patients using machine learning. I: European Heart Journal: Acute Cardiovascular Care. 2021 ; Bind 10, Nr. 8. s. 855-865.

Bibtex

@article{8f1e96d6f9fb4ca9bf054441fc08f19f,
title = "Improving 1-year mortality prediction in ACS patients using machine learning",
author = "Sebastian Weichwald and Alessandro Candreva and Rebekka Burkholz and Roland Klingenberg and Lorenz R{\"a}ber and Dik Heg and Robert Manka and Baris Gencer and Fran{\c c}ois Mach and David Nanchen and Nicolas Rodondi and Stephan Windecker and Reijo Laaksonen and Hazen, {Stanley L} and {Von Eckardstein}, Arnold and Frank Ruschitzka and L{\"u}scher, {Thomas F} and Buhmann, {Joachim M} and Matter, {Christian M}",
year = "2021",
doi = "10.1093/ehjacc/zuab030",
language = "English",
volume = "10",
pages = "855--865",
journal = "European Heart Journal: Acute Cardiovascular Care",
issn = "2048-8726",
publisher = "SAGE Publications",
number = "8",

}

RIS

TY - JOUR

T1 - Improving 1-year mortality prediction in ACS patients using machine learning

AU - Weichwald, Sebastian

AU - Candreva, Alessandro

AU - Burkholz, Rebekka

AU - Klingenberg, Roland

AU - Räber, Lorenz

AU - Heg, Dik

AU - Manka, Robert

AU - Gencer, Baris

AU - Mach, François

AU - Nanchen, David

AU - Rodondi, Nicolas

AU - Windecker, Stephan

AU - Laaksonen, Reijo

AU - Hazen, Stanley L

AU - Von Eckardstein, Arnold

AU - Ruschitzka, Frank

AU - Lüscher, Thomas F

AU - Buhmann, Joachim M

AU - Matter, Christian M

PY - 2021

Y1 - 2021

U2 - 10.1093/ehjacc/zuab030

DO - 10.1093/ehjacc/zuab030

M3 - Journal article

C2 - 34015112

VL - 10

SP - 855

EP - 865

JO - European Heart Journal: Acute Cardiovascular Care

JF - European Heart Journal: Acute Cardiovascular Care

SN - 2048-8726

IS - 8

ER -

ID: 305682575