Abstract
In the current paper we mathematically try to support the decision concerning the treatment with hyperbaric oxygen for patients, suffering from necrotizing fasciitis. To accomplish the task, we involve the fuzzified model of a quasi-perceptron, which is our modification of the classical artificial simple neuron. By means of the fuzzification of input signals and output decision levels, we wish to distinguish between decisions “treatment without recommended hyperbaric oxygen” versus “treatment with hyperbaric oxygen”. The number of decision levels can be arbitrary in order to extend the decision scale.
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Rakus-Andersson, E., Frey, J., Rutkowska, D. (2015). The Fuzzified Quasi-Perceptron in Decision Making Concerning Treatments in Necrotizing Fasciitis. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9120. Springer, Cham. https://doi.org/10.1007/978-3-319-19369-4_13
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DOI: https://doi.org/10.1007/978-3-319-19369-4_13
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