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- W2086815511 abstract "Abstract Alzheimer's disease (AD) and vascular dementia (VD) are the most common dementia. In this paper, we proposed a region selection for classification of AD, VD and normal (NOR) based on micro-Raman spectra fromplatelet. The preprocessing step is a smoothing followed by background elimination to the original spectra. Then we applied the minmax method for normalization. After the inspection of the preprocessed spectra, we found that 725-777, 1504-1592 and 1632-1700 cm -1 regions arethe most discriminative features in AD, VD and NOR spectra. We applied the feature transformation using PCA (principal component analysis) and NMF (nonnegative matrix factorization). The classification result of MAP(maximum a posteriori probability) involving 327 spectra transformed features using proposed local region showed about 92.8 % true classification average rate. Key Words : Alzheimer's disease, vascular dementia, feature transformation, Raman spectroscopy, pattern classification 본 논문은 교육과학기술부의 재원으로 한국연구재단의 지원을 받아 수행된 광역경제권 선도산업 인재양성 사업의 연구결과입니다." @default.
- W2086815511 created "2016-06-24" @default.
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- W2086815511 date "2011-11-30" @default.
- W2086815511 modified "2023-09-22" @default.
- W2086815511 title "Local Region Spectral Analysis for Performance Enhancement of Dementia Classification" @default.
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- W2086815511 doi "https://doi.org/10.5762/kais.2011.12.11.5150" @default.
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