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Title: Cardiovascular modeling and diagnostics

Abstract

In this paper, a novel approach to modeling and diagnosing the cardiovascular system is introduced. A model exhibits a subset of the dynamics of the cardiovascular behavior of an individual by using a recurrent artificial neural network. Potentially, a model will be incorporated into a cardiovascular diagnostic system. This approach is unique in that each cardiovascular model is developed from physiological measurements of an individual. Any differences between the modeled variables and the variables of an individual at a given time are used for diagnosis. This approach also exploits sensor fusion to optimize the utilization of biomedical sensors. The advantage of sensor fusion has been demonstrated in applications including control and diagnostics of mechanical and chemical processes.

Authors:
; ; ;  [1]
  1. Pacific Northwest Lab., Richland, WA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
OSTI Identifier:
377067
Report Number(s):
PNL-SA-26375; CONF-9503142-
ON: DE96009360; TRN: 96:003982-0024
DOE Contract Number:  
AC06-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: Workshop on environmental and energy applications of neural networks conference, Richland, WA (United States), 30-31 Mar 1995; Other Information: PBD: [1995]; Related Information: Is Part Of Applications of neural networks in environmental and energy sciences and engineering. Proceedings of the 1995 workshop on environmental and energy applications of neural networks; Hashem, S.; Keller, P.E.; Kouzes, R.T.; Kangas, L.J.; PB: 193 p.
Country of Publication:
United States
Language:
English
Subject:
55 BIOLOGY AND MEDICINE, BASIC STUDIES; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; DIAGNOSTIC TECHNIQUES; NEURAL NETWORKS; BIOLOGICAL MODELS; CARDIOVASCULAR SYSTEM; CARDIOVASCULAR DISEASES

Citation Formats

Kangas, L J, Keller, P E, Hashem, S, and Kouzes, R T. Cardiovascular modeling and diagnostics. United States: N. p., 1995. Web.
Kangas, L J, Keller, P E, Hashem, S, & Kouzes, R T. Cardiovascular modeling and diagnostics. United States.
Kangas, L J, Keller, P E, Hashem, S, and Kouzes, R T. 1995. "Cardiovascular modeling and diagnostics". United States. https://www.osti.gov/servlets/purl/377067.
@article{osti_377067,
title = {Cardiovascular modeling and diagnostics},
author = {Kangas, L J and Keller, P E and Hashem, S and Kouzes, R T},
abstractNote = {In this paper, a novel approach to modeling and diagnosing the cardiovascular system is introduced. A model exhibits a subset of the dynamics of the cardiovascular behavior of an individual by using a recurrent artificial neural network. Potentially, a model will be incorporated into a cardiovascular diagnostic system. This approach is unique in that each cardiovascular model is developed from physiological measurements of an individual. Any differences between the modeled variables and the variables of an individual at a given time are used for diagnosis. This approach also exploits sensor fusion to optimize the utilization of biomedical sensors. The advantage of sensor fusion has been demonstrated in applications including control and diagnostics of mechanical and chemical processes.},
doi = {},
url = {https://www.osti.gov/biblio/377067}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Dec 31 00:00:00 EST 1995},
month = {Sun Dec 31 00:00:00 EST 1995}
}

Conference:
Other availability
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