Details

Autor(en) / Beteiligte

• Tripoliti, Evanthia E.
• Karanasiou, Georgia S.
• Kalatzis, Fanis G.
• Bechlioulis, Aris
• Goletsis, Yorgos
• Naka, Katerina
• Fotiadis, Dimitrios I.

Titel

HEARTEN KMS – A knowledge management system targeting the management of patients with heart failure

Ist Teil von

• Journal of biomedical informatics, 2019-06, Vol.94, p.103203-103203, Article 103203

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2019

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• [Display omitted] •Assessment of the patient’s condition in terms of NYHA class.•Estimation of the patient’s medication, nutrition and physical activity adherence.•Prediction of potential adverse events.•Exploitation of information from breath and saliva biomarkers. The aim of this work is to present the HEARTEN Knowledge Management System, one of the core modules of the HEARTEN platform. The HEARTEN platform is an mHealth collaborative environment enabling the Heart Failure patients to self-manage the disease and remain adherent, while allowing the other ecosystem actors (healthcare professionals, caregivers, nutritionists, physical activity experts, psychologists) to monitor the patient’s health progress and offer personalized, predictive and preventive disease management. The HEARTEN Knowledge Management System is a tool which provides multiple functionalities to the ecosystem actors for the assessment of the patient’s condition, the estimation of the patient’s adherence, the prediction of potential adverse events, the calculation of Heart Failure related scores, the extraction of statistics, the association of patient clinical and non-clinical data and the provision of alerts and suggestions. The innovation of this tool lays in the analysis of multi-parametric personal data coming from different sources, including for the first time breath and saliva biomarkers, and the use of machine learning techniques. The HEARTEN Knowledge Management System consists of nine modules. The accuracy of the KMS modules ranges from 78% to 95% depending on the module/functionality.