Citation: Communication Papers of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 13, pages 51–55 (2017)
Abstract. The quality of data sets used in the classification process has a significant impact on the outcome. The noise contained in the input data depending on the nature and intensity may have a different effect on the classification result. This paper presents the results of research on the quality and reliability of arterio-venous fistula classification based on the signal recorded under controlled disturbance conditions and in the model of artificial disturbations. Typical environmental noise that may occur when the acoustic signal produced by the fistula was recorded and it is used as a disturbance. Its influence on the features extraction process and on the result of the fistula assessment was determined. Finally, a relationship between the intensity of the disturbances and the degree of shifting of the classification result to the pathological state of the fistula was demonstrated
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