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

This paper describes a processing technique that can be used to combine information from different medical analyses to discriminate between different pathologies that have similar symptoms. The paper is focused on the differentiation between asthma, bronchitis, and emphysema, using only functional noninvasive tests, but the proposed technique can be easily applied to other similar situations where different tests have to be used to identify a pathology. The technique is based on mixed neural-and-conventional processing that not only suggests the pathology, but also estimates the reliability of this suggestion.