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

J Biomed Inform

Department of Biomedical Research, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, GR 45110 Ioannina, Greece; Department of Materials Science and Engineering, Unit of Medical Technology and Intelligent Information Systems, University of Ioannina, GR 45110 Ioannina, Greece. Electronic address:

Published: June 2019

AI Article Synopsis

  • The HEARTEN Knowledge Management System is part of the HEARTEN platform designed to assist Heart Failure patients in self-managing their condition while allowing healthcare professionals to track and support their health.
  • This system provides tools for assessing patient conditions, monitoring adherence, predicting potential health issues, and generating personalized alerts, integrating data from various sources including novel breath and saliva biomarkers.
  • With nine modules that utilize machine learning, the system offers accuracy rates between 78% and 95%, enhancing disease management through advanced data analysis.

Article Abstract

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.

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http://dx.doi.org/10.1016/j.jbi.2019.103203DOI Listing

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