Multiparametric data analysis for diagnostic decision support in balance disorders

In this work we present a framework for the analysis and mining of multiparametric data related to balance disorders. The overall concept is to define the schema of the analysis that provides optimal results for diagnostic decision support in balance disorders. The work is part of the integrated EMBalance platform which targets the management of patients with balance disorders, from the diagnosis to treatment and evolution of the disease. The obtained results in four different balance disorders range from 76.4% to 92.1%.