Strategies in the use of static and dynamic Bayesian networks in home monitoring

Authors

C. Bescos, A. Schmeink, M. Harris, R. Schmidt,

Abstract

        This paper presents a methodology to use static and dynamic Bayesian Networks (BNs) in Decision Support Systems (DSS) for home monitoring. It consists of a loop around the patient, giving support both to the professional and to the patient in a more frequent follow-up.
The author presents the prototypes of a static BN for treatment guidance, and of a dynamic BN (DBN) for daily management and decompensation prediction in chronic Heart Failure (HF) patients. A validation with cardiologists for the selection and quantification of the input and output variables has been completed. The system will be validated using data from the MyHeart HF clinical study of one year of daily measurements of 200 patients.

BibTEX Reference Entry 

@inproceedings{BeScHaSc07,
	author = {Cristina Bescos and Anke Schmeink and Matthew Harris and Ralf Schmidt},
	title = "Strategies in the use of static and dynamic {B}ayesian networks in home monitoring",
	booktitle = "{IEEE} Benelux {EMBS} Symposium",
	address = {Heeze, the Netherlands},
	month = Dec,
	year = 2007,
	}

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