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PHEN : parkinson helper emergency notification system using Bayesian Belief Network

Mcheick Hamid, Khreiss Malak, Sweidan Hala et Zaarour Iyad. (2015). PHEN : parkinson helper emergency notification system using Bayesian Belief Network. Dans E-Technologies : 6th International Conference, MCETECH 2015, Montréal, QC, Canada, May 12-15, 2015, Proceedings. (p. 212-223). Cham, Suisse : Springer.

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URL officielle: http://dx.doi.org/doi:10.1007/978-3-319-17957-5_14

Résumé

Context-aware systems are used to aid users in their daily lives. In the recent years, researchers are exploring how context aware systems can benefit humanity through assist patients, specifically those who suffer incurable diseases, to cope with their illness. In this paper, we direct our work to help people who suffer from Parkinson disease. We propose PHEN, Parkinson Helper Engine Network System, a context-aware system that aims to support Parkinson disease patients on m any levels. We use ontology is for context representation and modeling. Then the ontology based context model is used to learn with Bayesian Belief network (BBN) which is beneficial in handling the uncertainty aspect of context-aware systems.

Type de document:Chapitre de livre
Date:2015
Lieu de publication:Cham, Suisse
Sujets:Sciences naturelles et génie > Sciences mathématiques > Informatique
Département, module, service et unité de recherche:Départements et modules > Département d'informatique et de mathématique
Éditeurs:Benyoucef, Morad
Weiss, Michael
Mili, Hafedh
Mots-clés:context-aware applications, Parkinson Disease, Health Care system, Bayesian Belief Network, Ubiquitous Computing, OWL, Tele-medicine
Informations complémentaires:Hamid Mcheick, Malak Khreiss, Hala Sweidan and Iyad Zaarour. PHEN: Parkinson Helper emergency Notification System Using Bayesian Belief Network, The 6th Montreal Conference on e-Technologies (MCETECH’2015), Springer Book: E-Technologies, Chapter: 14, DOI: 10.1007/978-3-319-17957-5_14, pp. 212-223, 2015
Déposé le:09 nov. 2016 01:12
Dernière modification:09 nov. 2016 01:12
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