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Quantitative EEG Markers of Entropy and Auto Mutual Information in Relation to MMSE Scores of Probable Alzheimer's Disease Patients.

, , , , , , , , , and . Entropy, 19 (3): 130 (2017)

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Explainable concept mappings of MRI: Revealing the mechanisms underlying deep learning-based brain disease classification., , , , , , , , , and 2 other author(s). CoRR, (2024)Individual classification of Alzheimer's disease with diffusion magnetic resonance imaging., , , , , , , , , and . NeuroImage, (2017)Quantitative EEG Markers of Entropy and Auto Mutual Information in Relation to MMSE Scores of Probable Alzheimer's Disease Patients., , , , , , , , , and . Entropy, 19 (3): 130 (2017)Learning Interpretable Regularized Ordinal Models from 3D Mesh Data for Neurodegenerative Disease Staging., , , , , , , , , and 32 other author(s). MLCN@MICCAI, volume 13596 of Lecture Notes in Computer Science, page 115-124. Springer, (2022)Electroencephalographic complexity markers explain neuropsychological test scores in Alzheimer's disease., , , , , , , , , and 4 other author(s). BHI, page 496-499. IEEE, (2014)Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer's Disease., , , , , , , , , and 3 other author(s). AIME, volume 10259 of Lecture Notes in Computer Science, page 65-75. Springer, (2017)A flexible method for the automated offline-detection of artifacts in multi-channel electroencephalogram recordings., , , , , , , and . EMBC, page 3793-3796. IEEE, (2017)Predicting rapid cognitive decline in Alzheimer's disease patients using quantitative EEG markers and neuropsychological test scores., , , , , , , , and . EMBC, page 6078-6081. IEEE, (2016)Using static and dynamic canonical correlation coefficients as quantitative EEG markers for Alzheimer's disease severity., , , , , , , , , and 4 other author(s). EMBC, page 2801-2804. IEEE, (2014)