Paper Info
Title
Estimation of Heart Failure Patients Medication Adherence through the Utilization of Saliva and Breath Biomarkers and Data Mining Techniques.
Abstract
The aim of this work is to estimate the medication adherence of patients with heart failure through the application of a data mining approach on a dataset including information from saliva and breath biomarkers. The method consists of two stages. In the first stage, a model for the estimation of adherence risk of a patient, exploiting anamnestic and instrumental data, is applied. In the second stage, the output of the model, accompanied with data from saliva and breath biomarkers, is given as input to a classification model for determining if the patient is adherent, in terms of medication. The method is evaluated on a dataset of 29 patients and the achieved accuracy is 96%.
Year
Venue
Field
2017
CBMS
Data modeling,Data mining,Heart failure,Biomarker (medicine),Saliva,Medicine
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
2
15
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
Roger Fuoco1022.46
Mario Marzilli1122.12
Maria Chiara Scali1200.68
Katerina K. Naka13207.99
Abdelhamid Errachid1423.81
Dimitrios I. Fotiadis15941121.32