Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome – the MADDEC study-Reference-Cited by-同舟云学术

Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome – the MADDEC study

Published:2019-02-17 Issue:2 Volume:51 Page:156-163
ISSN:0785-3890
Container-title:Annals of Medicine
language:en
Short-container-title:Annals of Medicine

Author:

Hernesniemi Jussi A.¹²,Mahdiani Shadi¹³,Tynkkynen Juho A.¹⁴,Lyytikäinen Leo-Pekka¹²⁵,Mishra Pashupati P.⁵,Lehtimäki Terho¹⁵,Eskola Markku²,Nikus Kjell¹²,Antila Kari³,Oksala Niku¹⁵⁶

Affiliation:

1. Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;

2. Department of Cardiology, Tays Heart Hospital, Tampere University Hospital, Tampere, Finland;

3. VTT Technical Research Center of Finland, Tampere, Finland;

4. Department of Radiology, Kanta-Häme Central Hospital, Hämeenlinna, Finland;

5. Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;

6. Vascular and Interventional Radiology Centre, Tampere University Hospital, Tampere, Finland

Funder

Business Finland research

University of Tampere

VTT Technical Research Center Finland Ltd

GE Healthcare Finland Ltd

Fimlab laboratories Ltd

Bittium Ltd and Politechinco di Milano

Competitive Research Funding of the Tampere University Hospital

Emil Aaltonen Foundation

the Academy of Finland

Finnish Foundation for Cardiovascular Research