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Clinical Decision Support Systems (CDSS) are becoming commonplace. They are used to alert doctors about drug interactions, to suggest possible diagnostics and in several other clinical situations. One of the approaches to building CDSS is by using techniques from the Knowledge Discovery from Databases (KDD) area. However using KDD for the construction of the knowledge base used in such systems, while reducing the maintenance work still demands repeated human intervention. In this work we present a KDD based architecture for CDSS for intensive care medicine. By resorting to automated data acquisition our architecture allows for the evaluation of the predictions made and subsequent action aiming at improving the predictive performance thus enhancing adaptive capacities. | 493.16 KB | Adobe PDF |
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Advisor(s)
Abstract(s)
Clinical Decision Support Systems (CDSS) are becoming commonplace. They are used to alert doctors about drug interactions, to suggest possible diagnostics and in several other clinical situations. One of the approaches to building CDSS is by using techniques from the Knowledge Discovery from Databases (KDD) area. However using KDD for the construction of the knowledge base used in such systems, while reducing the maintenance work still demands repeated human intervention. In this work we present a KDD based architecture for CDSS for intensive care medicine. By resorting to automated data acquisition our architecture allows for the evaluation of the predictions made and subsequent action aiming at improving the predictive performance thus enhancing adaptive capacities.
Description
https://scholar.google.com/scholar?q=Adaptive%20knowledge%20discovery%20for%20decision%20support%20in%20intensive%20care%20units
Keywords
Clinical Decision Support Intelligent Decision Support Systems Knowledge Discovery Intensive care Ensembles Multi-Agent Systems
Citation
Gago, P. E. D. R. O., & Santos, M. F. (2009). Adaptive knowledge discovery for decision support in intensive care units. WSEAS Transactions on Computers, 8(7), 1103-1112.
Publisher
World Scientific and Engineering Academy and Society (WSEAS)