This paper describes a processing technique that can be used to combine the pieces of information coming from different medical analyses. Such a technique is based on a mixed neural-and-conventional processing that allows both an easy neural network training and a robust estimation to be obtained. The paper is focused on the differentiation of asthma, bronchitis and emphysema by using functional non-invasive tests only, but the proposed technique can be easily applied to several different situations.
Mixed neural-conventional processing to differentiate airway diseases by means of functional non-invasive tests / Parvis, Marco; Gulotta, C; Tochio, R.. - STAMPA. - 1:(1999), pp. 93-98. (Intervento presentato al convegno 16th IEEE Instrumentation and Measurement Technology Conference, IMTC/99 - Measurements for the new Millenium tenutosi a Venice, Italy nel 24-26 June) [10.1109/IMTC.1999.776726].
Mixed neural-conventional processing to differentiate airway diseases by means of functional non-invasive tests
PARVIS, Marco;
1999
Abstract
This paper describes a processing technique that can be used to combine the pieces of information coming from different medical analyses. Such a technique is based on a mixed neural-and-conventional processing that allows both an easy neural network training and a robust estimation to be obtained. The paper is focused on the differentiation of asthma, bronchitis and emphysema by using functional non-invasive tests only, but the proposed technique can be easily applied to several different situations.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2499103
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