Paper Info
Title
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.
Year
DOI
Venue
2017
10.1109/EMBC.2017.8037648
2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Computer vision,Heart failure,Feature selection,Intensive care medicine,Biomarker (medicine),Artificial intelligence,Medical emergency,Medicine
Conference
2017
ISSN
Citations 
PageRank 
1094-687X
2
0.77
References 
Authors
0
16
Name
Order
Citations
PageRank
Evanthia E. Tripoliti18512.71
Theofilos G. Papadopoulos221.11
Georgia S. Karanasiou347.39
Fanis G. Kalatzis4124.13
Y. Goletsis512616.41
Aris Bechlioulis622.12
Silvia Ghimenti721.78
Tommaso Lomonaco822.46
Francesca Bellagambi921.78
Maria Giovanna Trivella10468.30
Roger Fuoco1122.46
Mario Marzilli1222.12
Maria Chiara Scali1320.77
Katerina K. Naka14207.99
Abdelhamid Errachid1523.81
Dimitrios I. Fotiadis16941121.32