| scholarly article | Q13442814 |
| P50 | author | Alzheimer's Disease Neuroimaging Initiative | Q4738819 |
| Joseph Buxbaum | Q15428933 | ||
| P2093 | author name string | Chunren Lai | |
| Congling Wu | |||
| Guiyin Cen | |||
| Shengwen Guo | |||
| P2860 | cites work | 18 F-FDG PET for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI) | Q24186399 |
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| Mild cognitive impairment represents early-stage Alzheimer disease | Q33938635 | ||
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| Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer's disease | Q34247849 | ||
| Improving CSF Biomarkers' Performance for Predicting Progression from Mild Cognitive Impairment to Alzheimer's Disease by Considering Different Confounding Factors: A Meta-Analysis | Q34349522 | ||
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| MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults | Q36304533 | ||
| The role of apolipoprotein E (APOE) genotype in early mild cognitive impairment (E-MCI). | Q36729508 | ||
| MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers | Q37158181 | ||
| Amyloid deposition, hypometabolism, and longitudinal cognitive decline | Q37207254 | ||
| Longitudinal pattern of regional brain volume change differentiates normal aging from MCI. | Q37213702 | ||
| FDG-PET changes in brain glucose metabolism from normal cognition to pathologically verified Alzheimer's disease | Q37415324 | ||
| Diagnostic accuracy of 18F-FDG and 11C-PIB-PET for prediction of short-term conversion to Alzheimer’s disease in subjects with mild cognitive impairment | Q37976853 | ||
| Patterns of 11C-PIB cerebral retention in mild cognitive impairment patients | Q38933150 | ||
| How early can we predict Alzheimer's disease using computational anatomy? | Q39377292 | ||
| Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment | Q39442854 | ||
| Combining MRI and CSF measures for classification of Alzheimer's disease and prediction of mild cognitive impairment conversion | Q39618253 | ||
| CSF p-Tau levels in the prediction of Alzheimer's disease. | Q41845685 | ||
| Sparse Multi-Task Regression and Feature Selection to Identify Brain Imaging Predictors for Memory Performance | Q42686467 | ||
| Relationship between atrophy and beta-amyloid deposition in Alzheimer disease | Q43107490 | ||
| Comparison of cortical thickness in patients with early-stage versus late-stage amnestic mild cognitive impairment. | Q44238793 | ||
| Sulcal morphology changes and their relationship with cortical thickness and gyral white matter volume in mild cognitive impairment and Alzheimer's disease | Q45252045 | ||
| Magnetic resonance spectroscopy as a predictor of conversion of mild cognitive impairment to dementia | Q45392070 | ||
| Conversion to dementia in mild cognitive impairment is associated with decline of N-actylaspartate and creatine as revealed by magnetic resonance spectroscopy. | Q46019129 | ||
| Conversion from mild cognitive impairment to probable Alzheimer's disease predicted by brain magnetic resonance spectroscopy | Q46412580 | ||
| Principal component analysis based on l1-norm maximization | Q47582537 | ||
| Geometrically accurate topology-correction of cortical surfaces using nonseparating loops | Q48207905 | ||
| Four subgroups of Alzheimer's disease based on patterns of atrophy using VBM and a unique pattern for early onset disease | Q48448564 | ||
| CSF biomarkers and medial temporal lobe atrophy predict dementia in mild cognitive impairment. | Q48494001 | ||
| Correlation of hippocampal volume and cognitive performances in patients with either mild cognitive impairment or Alzheimer's disease. | Q48591521 | ||
| White matter changes in mild cognitive impairment and AD: A diffusion tensor imaging study | Q48819183 | ||
| Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: a longitudinal MRI study | Q48832910 | ||
| Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex | Q48923978 | ||
| Structural and functional brain changes in the default mode network in subtypes of amnestic mild cognitive impairment | Q50680791 | ||
| Dimensionality reduced cortical features and their use in predicting longitudinal changes in Alzheimer's disease | Q50735664 | ||
| Robust Image Analysis With Sparse Representation on Quantized Visual Features | Q51317390 | ||
| A hybrid approach to the skull stripping problem in MRI. | Q51995443 | ||
| Topography of cortical thinning areas associated with hippocampal atrophy (HA) in patients with Alzheimer's disease (AD). | Q52618363 | ||
| Disrupted topological organization of resting-state functional brain network in subcortical vascular mild cognitive impairment | Q52662625 | ||
| Mild cognitive impairment (MCI) represents early-stage Alzheimer's disease. | Q53270841 | ||
| Apo-Eε4 allele in conjunction with Aβ42 and tau in CSF: biomarker for Alzheimer's disease | Q53315895 | ||
| Prediction of conversion from amnestic mild cognitive impairment to Alzheimer's disease using proton magnetic resonance spectroscopy | Q53351396 | ||
| Gene Selection for Cancer Classification using Support Vector Machines | Q56535529 | ||
| Genetic, Structural and Functional Imaging Biomarkers for Early Detection of Conversion from MCI to AD | Q85833584 | ||
| P2507 | corrigendum / erratum | Corrigendum: Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images | Q42355790 |
| P921 | main subject | mild cognitive impairment | Q1472703 |
| cognitive dysfunction | Q57859955 | ||
| P304 | page(s) | 146 | |
| P577 | publication date | 2017-05-18 | |
| P1433 | published in | Frontiers in Aging Neuroscience | Q21968084 |
| P1476 | title | Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images | |
| P478 | volume | 9 |
| Q92404020 | A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures |
| Q45944353 | Classifying MCI Subtypes in Community-Dwelling Elderly Using Cross-Sectional and Longitudinal MRI-Based Biomarkers. |
| Q42355790 | Corrigendum: Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images | main subject | P921 |
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