Methodology for Constructing a Short-Term Event Risk Score in Heart Failure Patients

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Applied Mathematics

ISSN Print: 2152-7385
ISSN Online: 2152-7393
www.scirp.org/journal/am
E-mail: am@scirp.org

Google-based Impact Factor: 0.96
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"Methodology for Constructing a Short-Term Event Risk Score in Heart Failure Patients"
written by Kévin Duarte, Jean-Marie Monnez, Eliane Albuisson,
published by Applied Mathematics, Vol.9 No.8, 2018

has been cited by the following article(s):

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CrossRef

[1]	Επεξεργασία και ανάλυση σημάτων τηλεπαρακολούθησης ασθενών για την πρόβλεψη ανεπιθύμητων συμβάντων με μεθόδους μηχανικής μάθησης
	2023

[2]	Construction of parsimonious event risk scores by an ensemble method. An illustration for short-term predictions in chronic heart failure patients from the GISSI-HF trial
	Applied Mathematics, 2021

[3]	Streaming constrained binary logistic regression with online standardized data
	2021

[4]	Construction and update of an online ensemble score involving linear discriminant analysis and logistic regression
	2021

[5]	A review of interpretable ML in healthcare: taxonomy, applications, challenges, and future directions
	Symmetry, 2021

[6]	Construction of parsimonious event risk scores by an ensemble method. An illustration for short-term predictions in chronic heart failure patients from the GISSI …
	Applied Mathematics, 2021

[7]	Full title:“Construction of parsimonious event risk scores by an ensemble method. An illustration for
	2020

[8]	Construction of parsimonious event risk scores by an ensemble method. An illustration for short-term predictions in chronic heart failure patients from the GISSI-HF trial …
	2020

[9]	Streaming constrained binary logistic regression with online standardized data. Application to scoring heart failure
	2019

[10]	Score de risque d'événement et score en ligne pour des insuffisants cardiaques
	SFC 2018 - XXVèmes Rencontres de la Société Francophone de Classification, 2018

[1]	Streaming constrained binary logistic regression with online standardized data Journal of Applied Statistics, 2022 DOI:10.1080/02664763.2020.1870672

[2]	A Review of Interpretable ML in Healthcare: Taxonomy, Applications, Challenges, and Future Directions Symmetry, 2021 DOI:10.3390/sym13122439

[3]	A Review of Interpretable ML in Healthcare: Taxonomy, Applications, Challenges, and Future Directions Symmetry, 2021 DOI:10.3390/sym13122439

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