Bayesian Classification of Cognitive Impairment Using fNIRS Measurement during Cognitive Tests
Author:
Affiliation:
1. Dept. of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology
2. National Center for Geriatrics and Gerontology
Publisher
Japanese Society for Artificial Intelligence
Subject
Artificial Intelligence,Software
Link
http://www.jstage.jst.go.jp/article/tjsai/27/2/27_2_28/_pdf
Reference15 articles.
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2. [de Leon 07] de Leon, M. J., Mosconi, L., De Santi, K. B. S., Zinkowski, R., Mehta, P. D., Pratico, D., et al.: Imaging and CSF studies in the preclinical diagnosis of Alzheimer's disease, Annals of New York Academy of Sciences, Vol. 1097, pp. 114-145 (2007)
3. [Draper 98] Draper, N. and Smith, H.: Applied Regression Analysis (3rd edition), John Wiley & Sons (1998)
4. “Mini-mental state”
5. [Ishiwata 06] Ishiwata, A., Sakayori, O., Minoshima, S., Mizumura, S., Kitamura, S., and Katayama, Y.: Preclinical evidence of Alzheimer changes in progressive mild cognitive impairment: a qualitative and quantitative SPECT study, Acta Neurologica Scandinavica;114(2):91-6, 2006, Vol. 114, No. 2, pp. 91-96 (2006)
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