Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12857/116040
Title: Monitoring asthma control in children with allergies by soft computing of lung function and exhaled nitric oxide
Authors: Pifferi, Massimo
Bush, Andrew
Pioggia, Giovanni
Di Cicco, Maria
Chinellato, Iolanda
Bodini, Alessandro 
Macchia, Pierantonio
Boner, Attilio L
Keywords Plus: FORCED EXPIRATORY VOLUME;RISK;SEVERITY;CLASSIFICATION;EXACERBATIONS;DIAGNOSIS;SYMPTOMS;EXPOSURE
Mesh headings: Asthma;Breath Tests;Neural Networks, Computer;Nitric Oxide
Secondary Mesh headings: Adolescent;Child;Cross-Sectional Studies;Exhalation;Female;Humans;Longitudinal Studies;Male;Predictive Value of Tests;Prospective Studies;Severity of Illness Index;Spirometry;Statistics, Nonparametric
Issue Date: Feb-2011
Publisher: ELSEVIER
Journal: Chest 
Abstract: 
Asthma control is emphasized by new guidelines but remains poor in many children. Evaluation of control relies on subjective patient recall and may be overestimated by health-care professionals. This study assessed the value of spirometry and fractional exhaled nitric oxide (FeNO) measurements, used alone or in combination, in models developed by a machine learning approach in the objective classification of asthma control according to Global Initiative for Asthma guidelines and tested the model in a second group of children with asthma.
URI: http://hdl.handle.net/20.500.12857/116040
ISSN: 00123692
DOI: 10.1378/chest.10-0992
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