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      Application of Evolutionary Fuzzy Cognitive Maps for Prediction of Pulmonary Infections

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          Abstract

          In this paper, a new evolutionary-based fuzzy cognitive map (FCM) methodology is proposed to cope with the forecasting of the patient states in the case of pulmonary infections. The goal of the research was to improve the efficiency of the prediction. This was succeeded with a new data fuzzification procedure for observables and optimization of gain of transformation function using the evolutionary learning for the construction of FCM model. The approach proposed in this paper was validated using real patient data from internal care unit. The results emerged had less prediction errors for the examined data records than those produced by the conventional genetic-based algorithmic approaches.

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          Author and article information

          Journal
          IEEE Transactions on Information Technology in Biomedicine
          IEEE Trans. Inform. Technol. Biomed.
          Institute of Electrical and Electronics Engineers (IEEE)
          1089-7771
          1558-0032
          January 2012
          January 2012
          : 16
          : 1
          : 143-149
          Article
          10.1109/TITB.2011.2175937
          22106153
          cfcb7f3a-7277-4ea9-bf1d-8607267fba62
          © 2012
          History

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