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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. 12 figs.

Inventors:
;
Issue Date:
Research Org.:
Battelle Memorial Institute
Sponsoring Org.:
USDOE, Washington, DC (United States)
OSTI Identifier:
541740
Patent Number(s):
5,680,866
Application Number:
PAN: 8-625,025
Assignee:
Battelle Memorial Inst., Richland, WA (United States) PTO; SCA: 550600; PA: EDB-97:142398; SN: 97001865584
DOE Contract Number:  
AC06-76RL01830
Resource Type:
Patent
Resource Relation:
Other Information: PBD: 28 Oct 1997
Country of Publication:
United States
Language:
English
Subject:
55 BIOLOGY AND MEDICINE, BASIC STUDIES; CARDIOVASCULAR DISEASES; NEURAL NETWORKS; DIAGNOSTIC TECHNIQUES; DIAGNOSIS; MULTIVARIATE ANALYSIS; MEDICINE

Citation Formats

Kangas, L.J., and Keller, P.E. Artificial neural network cardiopulmonary modeling and diagnosis. United States: N. p., 1997. Web.
Kangas, L.J., & Keller, P.E. Artificial neural network cardiopulmonary modeling and diagnosis. United States.
Kangas, L.J., and Keller, P.E. Tue . "Artificial neural network cardiopulmonary modeling and diagnosis". United States.
@article{osti_541740,
title = {Artificial neural network cardiopulmonary modeling and diagnosis},
author = {Kangas, L.J. and Keller, P.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. 12 figs.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1997},
month = {10}
}