Correction to: Predicting survival in heart failure: a risk score based on machine-learning and change point algorithm (Clinical Research in Cardiology, (2021), 110, 8, (1321-1333), 10.1007/s00392-021-01870-7)

Wonse Kim, Jin Joo Park, Hae Young Lee, Kye Hun Kim, Byung Su Yoo, Seok Min Kang, Sang Hong Baek, Eun Seok Jeon, Jae Joong Kim, Myeong Chan Cho, Shung Chull Chae, Byung Hee Oh, Woong Kook, Dong Ju Choi

Research output: Contribution to journalComment/debatepeer-review

Abstract

In the Funding Section, the Following Information Was Missing: This Work Was Also Supported By the National Research Foundation of Korea [2017R1A5A1015626, 2018R1A2A3075511]. The Entire Section Reads: Funding This work was supported by Research of Korea Centers for Disease Control and Prevention [2010- E63003-00, 2011-E63002-00, 2012-E63005-00, 2013- E63003-00, 2013-E63003-01, 2013-E63003- 02, and 2016- ER6303-00]. This work was also supported by the National Research Foundation of Korea [2017R1A5A1015626, 2018R1A2A3075511, 2020R1I1A1A01073151]. The original article has been corrected.

Original languageEnglish
Pages (from-to)473
Number of pages1
JournalClinical Research in Cardiology
Volume111
Issue number4
DOIs
Publication statusPublished - 2022 Apr

Bibliographical note

Publisher Copyright:
© Springer-Verlag GmbH Germany, part of Springer Nature 2021.

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine

Fingerprint

Dive into the research topics of 'Correction to: Predicting survival in heart failure: a risk score based on machine-learning and change point algorithm (Clinical Research in Cardiology, (2021), 110, 8, (1321-1333), 10.1007/s00392-021-01870-7)'. Together they form a unique fingerprint.

Cite this