Multi-step prediction of pulmonary infection with the use of evolutionary fuzzy cognitive maps

dc.contributor.author	Παπαγεωργίου, Ελπινίκη Ι.	el
dc.contributor.author	Froelich, Wojciech	en
dc.date.accessioned	2015-05-24T10:43:14Z
dc.date.available	2015-05-24T10:43:14Z
dc.date.issued	2015-05-24
dc.identifier.uri	http://hdl.handle.net/11400/11032
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.sciencedirect.com/science/article/pii/S0925231212000847	en
dc.subject	Pulmonary infection
dc.subject	Prediction
dc.subject	Πνευμονική λοίμωξη
dc.subject	Πρόβλεψη
dc.title	Multi-step prediction of pulmonary infection with the use of evolutionary fuzzy cognitive maps	en
heal.type	journalArticle
heal.classification	Technology
heal.classification	Computer science
heal.classification	Τεχνολογία
heal.classification	Πληροφορική
heal.classificationURI	http://zbw.eu/stw/descriptor/10470-6
heal.classificationURI	http://data.seab.gr/concepts/77de68daecd823babbb58edb1c8e14d7106e83bb
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Πληροφορική
heal.identifier.secondary	doi:10.1016/j.neucom.2011.08.034
heal.language	en
heal.access	campus
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Πληροφορικής Τ.Ε.	el
heal.publicationDate	2012
heal.bibliographicCitation	Papageorgiou, E. and Froelich, W. (September 2012). Multi-step prediction of pulmonary infection with the use of evolutionary fuzzy cognitive maps. Neurocomputing. 92. pp. 28-35. Elsevier B.V: 2012. Available from: http://www.sciencedirect.com/science/article/pii/S0925231212000847 [Accessed 22/02/2012]	en
heal.abstract	The task of prediction in the medical domain is a very complex one, considering the level of vagueness and uncertainty management. The main objective of the presented research is the multi-step prediction of state of pulmonary infection with the use of a predictive model learnt on the basis of changing with time data. The contribution of this paper is twofold. In the application domain, in order to predict the state of pneumonia, the approach of fuzzy cognitive maps (FCMs) is proposed as an easy of use, interpretable, and flexible predictive model. In the theoretical part, addressing the requirements of the medical problem, a multi-step enhancement of the evolutionary algorithm applied to learn the FCM was introduced. The advantage of using our method was justified theoretically and then verified experimentally. The results of our investigation seem to be encouraging, presenting the advantage of using the proposed multi-step prediction approach.	en
heal.publisher	Elsevier B.V.	en
heal.journalName	Neurocomputing	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true