Experts' knowledge acquisition for differential diagnostics of bronchial asthma in children in STEPCLASS environment

Abstract

The problem of experts' knowledge acquisition for diagnostic decision support systems (DDSS) is considered as a multi-attribute classification problem (MACP), where a class is the subset of objects with the same diagnosis. Method STEPCLASS has proved to be an effective tool for such problem solving in various applications due to its ability to construct complete (up to the experts' knowledge) and contradiction-free knowledge bases. The main techniques of STEPCLASS – application domain structuring, large-size problem decomposition, classification rules eliciting, and rules' inconsistency control – are considered and illustrated with its application for constructing knowledge base of DDSS for differential diagnostics of bronchial asthma in children (DDBAC).