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Alzheimer's disease (AD) is a progressive brain disease. Accurate detection of AD and its prodromal stage, mild cognitive impairment (MCI), are crucial. There is also a growing interest in identifying

Alzheimer's disease (AD) is a progressive brain disease. Accurate detection of AD and its prodromal stage, mild cognitive impairment (MCI), are crucial. There is also a growing interest in identifying brain imaging biomarkers that help to automatically differentiate stages of Alzheimer's disease. Here, we focused on brain structural networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression.

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    Date Created
    • 2015-07-24
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  • Text
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    Identifier
    • Digital object identifier: 10.3389/fnins.2015.00257
    • Identifier Type
      International standard serial number
      Identifier Value
      1662-4548
    • Identifier Type
      International standard serial number
      Identifier Value
      1662-453X

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    Zhan, L., Liu, Y., Wang, Y., Zhou, J., Jahanshad, N., Ye, J., & Thompson, P. M. (2015). Boosting brain connectome classification accuracy in Alzheimers disease using higher-order singular value decomposition. Frontiers in Neuroscience, 9. doi:10.3389/fnins.2015.00257

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