A computational approach for the estimation of heart failure patients status using saliva biomarkers

Abstract : The aim of this work is to present a computational approach for the estimation of the severity of heart failure (HF) in terms of New York Heart Association (NYHA) class and the characterization of the status of the HF patients, during hospitalization, as acute, progressive or stable. The proposed method employs feature selection and classification techniques. However, it is differentiated from the methods reported in the literature since it exploits information that biomarkers fetch. The method is evaluated on a dataset of 29 patients, through a 10-fold-cross-validation approach. The accuracy is 94 and 77% for the estimation of HF severity and the status of HF patients during hospitalization, respectively.
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https://hal.archives-ouvertes.fr/hal-01767411
Contributor : Agnès Bussy <>
Submitted on : Monday, April 16, 2018 - 11:08:51 AM
Last modification on : Tuesday, February 26, 2019 - 10:54:02 AM

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Evanthia Tripoliti, Theofilos Papadopoulos, Georgia Karanasiou, Fanis Kalatzis, Yorgos Goletsis, et al.. A computational approach for the estimation of heart failure patients status using saliva biomarkers. IEEE. 39th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Jul 2017, South Korea. pp.3648-3651, 2017, PROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, 978-1-5090-2809-2. ⟨10.1109/EMBC.2017.8037648⟩. ⟨hal-01767411⟩

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