Abstract
This paper presents knowledge discovery from fMRI brain images. The algorithm for the discovery is the Logical Regression Analysis, which consists of two steps. The first step is regression analysis. The second step is rule extraction from the regression formula obtained by the regression analysis. In this paper, we use nonparametric regression analysis as a regression analysis, since there are not sufficient data in knowledge discovery from fMRI brain images. The algorithm has been applied to two experimental tasks, finger tapping and calculation. Experimental results show that the algorithm has rediscovered well-known facts and discovered new facts.
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© 2000 Springer-Verlag Berlin Heidelberg
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Tsukimoto, H., Kakimoto, M., Morita, C., Kikuchi, Y., Hatakeyama, E., Miyazaki, Y. (2000). Knowledge Discovery from fMRI Brain Images by Logical Regression Analysis. In: Arikawa, S., Morishita, S. (eds) Discovery Science. DS 2000. Lecture Notes in Computer Science(), vol 1967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44418-1_17
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DOI: https://doi.org/10.1007/3-540-44418-1_17
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