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.
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Marin-Alonso, O., Ruiz-Fernández, D., Soriano-Paya, A. (2015). Abstracting Classification Models Heterogeneity to Build Clinical Group Diagnosis Support Systems. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo-Moreo, F., Adeli, H. (eds) Artificial Computation in Biology and Medicine. IWINAC 2015. Lecture Notes in Computer Science(), vol 9107. Springer, Cham. https://doi.org/10.1007/978-3-319-18914-7_28
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DOI: https://doi.org/10.1007/978-3-319-18914-7_28
Publisher Name: Springer, Cham
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