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1 Ergebnisse
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A machine learning model to predict the risk of 30-day read..:
Sara Bersche Golas
;
Takuma Shibahara
;
Stephen Agboola
...
http://link.springer.com/article/10.1186/s12911-018-0620-z. , 2018
Link:
https://doi.org/10.1186/s12911-018-0620-z
RT Journal T1
A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:e61ab19542af4605a2b0fb04e53509c9&Exemplar=1&LAN=DE A1 Sara Bersche Golas A1 Takuma Shibahara A1 Stephen Agboola A1 Hiroko Otaki A1 Jumpei Sato A1 Tatsuya Nakae A1 Toru Hisamitsu A1 Go Kojima A1 Jennifer Felsted A1 Sujay Kakarmath A1 Joseph Kvedar A1 Kamal Jethwani PB BMC YR 2018 K1 Heart failure K1 Machine learning K1 Deep learning K1 Deep unified networks K1 Readmission reduction K1 Value-based care K1 Computer applications to medicine. Medical informatics K1 R858-859.7 JF http://link.springer.com/article/10.1186/s12911-018-0620-z LK http://dx.doi.org/https://doi.org/10.1186/s12911-018-0620-z DO https://doi.org/10.1186/s12911-018-0620-z SF ELIB - SuUB Bremen
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