Medical Decision Support Tool from a Fuzzy-Rules Driven Bayesian Network

Vasilios Zarikas, Elpiniki Papageorgiou, Damira Pernebayeva, Nurislam Tursynbek

2018

Abstract

The task of carrying out an effective and efficient decision on medical domain is a complex one, since a lot of uncertainty and vagueness is involved. Fuzzy logic and probabilistic methods for handling uncertain and imprecise data both provide an advance towards the goal of constructing an intelligent decision support system (DSS) for medical diagnosis and therapy. This work reports on a successfully developed DSS concerning pneumonia disease. A detailed and clear description of the reasoning behind the core decision making module of the DSS, is included, depicting the proposed methodological issues. The results have shown that the suggested methodology for constructing bayesian networks (BNs) from fuzzy rules gives a front-end decision about the severity of pulmonary infections, providing similar results to those obtained with physicians’ intuition.

Paper Citation

in Harvard Style

Zarikas V., Papageorgiou E., Pernebayeva D. and Tursynbek N. (2018). Medical Decision Support Tool from a Fuzzy-Rules Driven Bayesian Network.In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-275-2, pages 539-549. DOI: 10.5220/0006642705390549

in Bibtex Style

@conference{icaart18,
author={Vasilios Zarikas and Elpiniki Papageorgiou and Damira Pernebayeva and Nurislam Tursynbek},
title={Medical Decision Support Tool from a Fuzzy-Rules Driven Bayesian Network},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2018},
pages={539-549},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006642705390549},
isbn={978-989-758-275-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Medical Decision Support Tool from a Fuzzy-Rules Driven Bayesian Network
SN - 978-989-758-275-2
AU - Zarikas V.
AU - Papageorgiou E.
AU - Pernebayeva D.
AU - Tursynbek N.
PY - 2018
SP - 539
EP - 549
DO - 10.5220/0006642705390549