Fusion de données avec des réseaux bayésiens pour la modélisation des systèmes dynamiques et son application en télémédecine

Abstract : This thesis presents a new approach of data fusion in the context of probabilistic diagnosis in telemedicine. Our contribution is a new definition of qualified gain in a data fusion process, and an application of dynamic bayesian network to medical diagnosis. This approach forms a general framework for our purpose : medical diagnosis. The Diatelic project's goal is to assist kidney disease people at home by monitoring their hydration rate. Dynamic bayesian networks are used to modelize uncertain and dynamical using the strong probabilistic formalism. For this purpose, we have developped a bayesian engine, to deal with our experiments. The Diatelic[exposant]TM (v3) has been implemented with it. Health state of the patient could be regulated through the use of this system. New problems have arise during this PhD thesis work: on-line models adaptation, quantifying the data fusion gain and dealing with multiple time-scale bayesian networks.
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David Bellot. Fusion de données avec des réseaux bayésiens pour la modélisation des systèmes dynamiques et son application en télémédecine. Autre [cs.OH]. Université Henri Poincaré - Nancy 1, 2002. Français. ⟨NNT : 2002NAN10248⟩. ⟨tel-01754389⟩

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