Abstracting classification models heterogeneity to build clinical group diagnosis support systems

Abstract

Many diagnosis support systems (DSS) are focused on precise disorders, being not useful for differential diagnosis (DD) or facing comorbidities. Few DSSs offer a rich list of potential diagnoses and they do not reflect complex relations between diseases to be diagnosed. We present a model to allow collaboration of multiple heterogeneous diagnostic units (DU), which are actual DSSs, behaving as a whole system. The heterogeneity of the DUs refers to the disease they diagnose and the classification model they use to do so. This model offers a framework to build multi-purpose DSSs, assuring their operability and functioning despite the heterogeneity of the single diagnostic units.