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.

Monitoring asthma control in children with allergies by soft computing of lung function and exhaled nitric oxide

Di Cicco, Maria;
2011

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.
Pifferi, Massimo; Bush, Andrew; Pioggia, Giovanni; Di Cicco, Maria; Chinellato, Iolanda; Bodini, Alessandro; Macchia, Pierantonio; Boner, Attilio L
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/949378
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