Mixed neural-conventional processing to differentiate airway diseases by means of functional non-invasive tests

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