EEG Classification of Mild and Severe Alzheimer's Disease Using Parallel Factor Analysis Method

[1]  Andrzej Cichocki,et al.  Nonnegative Matrix and Tensor Factorization T , 2007 .

[2]  S. Amari,et al.  Nonnegative Matrix and Tensor Factorization [Lecture Notes] , 2008, IEEE Signal Processing Magazine.

[3]  Anthony C. Atkinson,et al.  Exploratory tools for clustering multivariate data , 2007, Comput. Stat. Data Anal..

[4]  Andrzej Cichocki,et al.  Nonnegative Tensor Factorization for Continuous EEG Classification , 2007, Int. J. Neural Syst..

[5]  Rasmus Bro,et al.  Multiway analysis of epilepsy tensors , 2007, ISMB/ECCB.

[6]  Paolo Massimo Buscema,et al.  The IFAST model, a novel parallel nonlinear EEG analysis technique, distinguishes mild cognitive impairment and Alzheimer's disease patients with high degree of accuracy , 2007, Artif. Intell. Medicine.

[7]  A. Cichocki,et al.  Techniques for early detection of Alzheimer's disease using spontaneous EEG recordings , 2007, Physiological measurement.

[8]  C. Mathers,et al.  Global prevalence of dementia: a Delphi consensus study , 2005, The Lancet.

[9]  A. Cichocki,et al.  EEG filtering based on blind source separation (BSS) for early detection of Alzheimer's disease , 2005, Clinical Neurophysiology.

[10]  R. Bro,et al.  A new efficient method for determining the number of components in PARAFAC models , 2003 .

[11]  W. Shankle,et al.  A new EEG method for estimating cortical neuronal impairment that is sensitive to early stage Alzheimer's disease , 2002, Clinical Neurophysiology.

[12]  G. Alexander,et al.  Longitudinal PET Evaluation of Cerebral Metabolic Decline in Dementia: A Potential Outcome Measure in Alzheimer's Disease Treatment Studies. , 2002, The American journal of psychiatry.

[13]  Lars Bertram,et al.  New Frontiers in Alzheimer's Disease Genetics , 2001, Neuron.

[14]  K. Blennow,et al.  Evaluation of CSF-tau and CSF-Abeta42 as diagnostic markers for Alzheimer disease in clinical practice. , 2001, Archives of neurology.

[15]  T Dierks,et al.  Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study , 2000, Clinical Neurophysiology.

[16]  Rasmus Bro,et al.  The N-way Toolbox for MATLAB , 2000 .

[17]  R. Bro,et al.  PARAFAC2—Part I. A direct fitting algorithm for the PARAFAC2 model , 1999 .

[18]  R. Bro PARAFAC. Tutorial and applications , 1997 .

[19]  E P Sloan,et al.  Electroencephalography and single photon emission computed tomography in dementia: a comparative study , 1995, Psychological Medicine.

[20]  S Lehéricy,et al.  Memory disorders in probable Alzheimer's disease: the role of hippocampal atrophy as shown with MRI. , 1995, Journal of neurology, neurosurgery, and psychiatry.

[21]  K. Coburn,et al.  EEG-based, neural-net predictive classification of Alzheimer's disease versus control subjects is augmented by non-linear EEG measures. , 1994, Electroencephalography and clinical neurophysiology.

[22]  L. Berg,et al.  Frequency analysis of the resting awake EEG in mild senile dementia of Alzheimer type. , 1983, Electroencephalography and clinical neurophysiology.