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%.

Estimation of Heart Failure Patients Medication Adherence through the Utilization of Saliva and Breath Biomarkers and Data Mining Techniques

Silvia Ghimenti;Tommaso Lomonaco;Roger Fuoco;Mario Marzilli;Errachid El Salhi, Abdelhamid;
2017-01-01

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%.
2017
978-1-5386-1710-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/910389
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