A Home-based Early Risk Detection System for Congestive Heart Failure using a Bayesian Reasoning Network

Athanasia Lappa, Christos Goumopoulos

2017

Abstract

Congestive heart failure (CHF) is a progressive condition in which the heart is no longer capable of supplying adequate oxygenated blood to the body. Since the incidence of CHF increases with age, mainly due to the development of heart failure risk factors the epidemic of CHF is expected to grow further in the coming decades and thus becoming an important public health problem. In this paper we present a risk detection system for CHF that uses a Bayesian Network (BN) combined with health measurements that can be taken in a home environment using ambient assisted living technologies. The algorithm is empowered by employing statistical and medical analysis of the stored biological data and the output can be used as a basis for triggering proper preventive interventions. The BN design was established by surveying the relevant literature and consulting the domain expert. The network content combines both biometric variables that are daily monitored and data from patient’s clinical history as well as additional heart failure risk factors in terms of the EuroSCORE model. The predictive validity was tested with the involvement of the domain expert who specified proper validation rules in terms of criteria for detecting a CHF risk.

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  26. Female 0.2196434 =55 0.3491475 ECA 0.5360268 Urgency
  27. CPD 0.1886564 Urgent 0.3174673 N/M mob 0.2407181 Emergency 0.7039121 Redo 01.118599 Salvage 1.362947 Renal dysfunction Weight of procedure On dialysis 0.6421508 1 non-CABG 0.0062118 CC = 50 0.8592256 2 0.5521478 CC 50-85 0.303553 3+ 0.9724533 AE 0.6194522 Thoracic aorta 0.6527205 Critical 1.086517 Constant -5.324537 For age, xi = 1 if patient age = 60; xi increases by one point per year thereafter (xi = 2 if age 61; xi = 3 if age 62 etc.).
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Paper Citation


in Harvard Style

Lappa A. and Goumopoulos C. (2017). A Home-based Early Risk Detection System for Congestive Heart Failure using a Bayesian Reasoning Network . In Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE, ISBN 978-989-758-251-6, pages 58-69. DOI: 10.5220/0006300300580069


in Bibtex Style

@conference{ict4awe17,
author={Athanasia Lappa and Christos Goumopoulos},
title={A Home-based Early Risk Detection System for Congestive Heart Failure using a Bayesian Reasoning Network},
booktitle={Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,},
year={2017},
pages={58-69},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006300300580069},
isbn={978-989-758-251-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,
TI - A Home-based Early Risk Detection System for Congestive Heart Failure using a Bayesian Reasoning Network
SN - 978-989-758-251-6
AU - Lappa A.
AU - Goumopoulos C.
PY - 2017
SP - 58
EP - 69
DO - 10.5220/0006300300580069