2008
DOI: 10.1007/s10916-008-9196-y
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Prediction of Forced Expiratory Volume in Pulmonary Function Test using Radial Basis Neural Networks and k-means Clustering

Abstract: In this work, prediction of forced expiratory volume in pulmonary function test, carried out using spirometry and neural networks is presented. The pulmonary function data were recorded from volunteers using commercial available flow volume spirometer in standard acquisition protocol. The Radial Basis Function neural networks were used to predict forced expiratory volume in 1 s (FEV1) from the recorded flow volume curves. The optimal centres of the hidden layer of radial basis function were determined by k-mea… Show more

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Cited by 12 publications
(7 citation statements)
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“…Previous work found machine learning methods can predict smoking cessation and forced expiratory volume in one second (FEV 1 ), a spirometric measure used to determine COPD severity [ 2 4 ]. In particular, radial basis neural network predicted FEV 1 using spirometry data [ 5 ], and spirometry and demographic data [ 6 ], and the predicted and actual FEV 1 values were highly correlated. However, prediction accuracy was better for normal rather than restrictive or obstructive diseased condition [ 5 , 6 ].…”
Section: Introductionmentioning
confidence: 99%
“…Previous work found machine learning methods can predict smoking cessation and forced expiratory volume in one second (FEV 1 ), a spirometric measure used to determine COPD severity [ 2 4 ]. In particular, radial basis neural network predicted FEV 1 using spirometry data [ 5 ], and spirometry and demographic data [ 6 ], and the predicted and actual FEV 1 values were highly correlated. However, prediction accuracy was better for normal rather than restrictive or obstructive diseased condition [ 5 , 6 ].…”
Section: Introductionmentioning
confidence: 99%
“…17% of these deaths related to lung system and respiratory diseases as one of the main causes of death in workplace settings next to circulatory diseases (31%) and malignant neoplasms (26%) 1 . Commonly for assessing pulmonary function parameters and health status lung system used pulmonary functional tests 2,3 . These tests can monitor the presence and absence of pulmonary function abnormalities in early diagnoses of lung diseases 2,4 .…”
Section: Introductionmentioning
confidence: 99%
“…Commonly for assessing pulmonary function parameters and health status lung system used pulmonary functional tests 2,3 . These tests can monitor the presence and absence of pulmonary function abnormalities in early diagnoses of lung diseases 2,4 . In workplaces, spirometry is a primary and valuable tool for diagnosing pulmonary diseases 5 .…”
Section: Introductionmentioning
confidence: 99%
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