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Title: Artificial neural network cardiopulmonary modeling and diagnosis

Abstract

The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis.

Inventors:
 [1];  [1]
  1. (Richland, WA)
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA
OSTI Identifier:
871203
Patent Number(s):
US 5680866
Assignee:
Battelle Memorial Institute (Richland, WA) PNNL
DOE Contract Number:  
AC06-76RL01830
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
artificial; neural; network; cardiopulmonary; modeling; diagnosis; method; diagnosing; condition; individual; comparing; data; progressive; multi-stage; non-linear; multi-variate; model; preferably; recurrent; sensor; fusion; relies; cardiovascular; developed; physiological; measurements; differences; modeled; parameters; time; artificial neural; neural network; neural net; /600/706/

Citation Formats

Kangas, Lars J., and Keller, Paul E. Artificial neural network cardiopulmonary modeling and diagnosis. United States: N. p., 1997. Web.
Kangas, Lars J., & Keller, Paul E. Artificial neural network cardiopulmonary modeling and diagnosis. United States.
Kangas, Lars J., and Keller, Paul E. Wed . "Artificial neural network cardiopulmonary modeling and diagnosis". United States. https://www.osti.gov/servlets/purl/871203.
@article{osti_871203,
title = {Artificial neural network cardiopulmonary modeling and diagnosis},
author = {Kangas, Lars J. and Keller, Paul E.},
abstractNote = {The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1997},
month = {1}
}

Patent:

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