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%.
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Submitted on : Wednesday, August 22, 2018 - 10:37:35 AM
Last modification on : Tuesday, February 26, 2019 - 10:54:02 AM

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Evanthia Eleftherios Tripoliti, Theofilos Papadopoulos, Georgia Karanasiou, Fanis Kalatzis, Dimitrios Ioannis Fotiadis, et al.. Estimation of Heart Failure Patients Medication Adherence through the Utilization of Saliva and Breath Biomarkers and Data Mining Techniques. Bamidis PD, Konstantinidis ST, Rodrigues PP. 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), Jun 2017, Thessaloniki, Greece. Proceedings Papers 2017 IEEE - 30th IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS), IEEE, pp.231-235, 2017, 978-1-5386-1710-6. ⟨10.1109/CBMS.2017.68⟩. ⟨hal-01859491⟩

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