1
Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer’s disease: Machine learning approaches
2
A Conformation Variant of p53 Combined with Machine Learning Identifies Alzheimer Disease in Preclinical and Prodromal Stages
3
Body Fluid Biomarkers for Alzheimer’s Disease—An Up-To-Date Overview
4
Significance of Blood and Cerebrospinal Fluid Biomarkers for Alzheimer’s Disease: Sensitivity, Specificity and Potential for Clinical Use
5
Biomarkers for Alzheimer’s Disease Early Diagnosis
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Application of modern neuroimaging technology in the diagnosis and study of Alzheimer's disease
7
Deep learning detection of informative features in tau PET for Alzheimer’s disease classification
8
Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases
9
An Ensemble Approach to Predict Schizophrenia Using Protein Data in the N-methyl-D-Aspartate Receptor (NMDAR) and Tryptophan Catabolic Pathways
10
Development and validation of an interpretable deep learning framework for Alzheimer’s disease classification
11
Application and Assessment of Deep Learning for the Generation of Potential NMDA Receptor Antagonists
12
Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches
13
Reduced Hippocampal Glutamate and Posterior Cingulate N-Acetyl Aspartate in Mild Cognitive Impairment and Alzheimer’s Disease Is Associated with Episodic Memory Performance and White Matter Integrity in the Cingulum: A Pilot Study
14
D-glutamate, D-serine, and D-alanine differ in their roles in cognitive decline in patients with Alzheimer's disease or mild cognitive impairment
15
Glutamatergic response to a low load working memory paradigm in the left dorsolateral prefrontal cortex in patients with mild cognitive impairment: a functional magnetic resonance spectroscopy study
16
Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer’s Disease biomarker discovery cohort
17
Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data
18
Adherence to multidomain interventions for dementia prevention: Data from the FINGER and MAPT trials
19
The Alzheimer's Disease Clinical Spectrum: Diagnosis and Management.
20
Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology
21
A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort
22
Combination of G72 Genetic Variation and G72 Protein Level to Detect Schizophrenia: Machine Learning Approaches
23
Questions concerning the role of amyloid-β in the definition, aetiology and diagnosis of Alzheimer’s disease
24
Machine Learning Approaches for Clinical Psychology and Psychiatry.
25
Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study
26
Development and validation of a novel dementia of Alzheimer's type (DAT) score based on metabolism FDG-PET imaging
27
Blood levels of D-amino acid oxidase vs. D-amino acids in reflecting cognitive aging
28
Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity
29
An overview on d-amino acids
30
Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging
31
Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials
32
CSF tau and the CSF tau/ABeta ratio for the diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).
33
Alzheimer's disease and other dementias: update on research
34
Role of Glutamate and NMDA Receptors in Alzheimer’s Disease
35
In vivo cortical spreading pattern of tau and amyloid in the Alzheimer disease spectrum
36
Regional profiles of the candidate tau PET ligand 18F-AV-1451 recapitulate key features of Braak histopathological stages.
37
Biomarkers in the Diagnosis and Prognosis of Alzheimer’s Disease
38
Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion‐Tensor and Magnetic Resonance Imaging Data
39
d-serine levels in Alzheimer's disease: implications for novel biomarker development
40
Mild to moderate Alzheimer dementia with insufficient neuropathological changes
41
D-serine increases adult hippocampal neurogenesis
42
D-Serine: physiology and pathology
43
Brain d-amino acids: a novel class of neuromodulators
44
Accuracy of the Clinical Diagnosis of Alzheimer Disease at National Institute on Aging Alzheimer Disease Centers, 2005–2010
45
Overview of glutamatergic neurotransmission in the nervous system
46
Soluble Aβ Oligomers Inhibit Long-Term Potentiation through a Mechanism Involving Excessive Activation of Extrasynaptic NR2B-Containing NMDA Receptors
47
The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease
48
Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease
49
Cerebrospinal fluid and plasma biomarkers in Alzheimer disease
50
The clinical use of structural MRI in Alzheimer disease
51
Faculty Opinions recommendation of Soluble oligomers of amyloid Beta protein facilitate hippocampal long-term depression by disrupting neuronal glutamate uptake.
52
Memory and the NMDA receptors.
53
Neuropathology of nondemented aging: Presumptive evidence for preclinical Alzheimer disease
54
d‐Amino acids in the brain: d‐serine in neurotransmission and neurodegeneration
55
Natural Oligomers of the Alzheimer Amyloid-β Protein Induce Reversible Synapse Loss by Modulating an NMDA-Type Glutamate Receptor-Dependent Signaling Pathway
56
Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry
57
Pathways towards and away from Alzheimer's disease
58
Glutamate and the glutamate receptor system: a target for drug action
59
Glutamate receptor function in learning and memory
61
M / EEG-based Biomarkers to predict the Mild Cognitive Impairment and Alzheimer ' s disease : A Review from the Machine Learning Perspective
62
Data Mining and Machine Learning Methods for Dementia Research.
63
Prevalence of Alzheimer disease in US states.
64
Core candidate neurochemical and imaging biomarkers of Alzheimer's disease. Alzheimer's Dement
65
Free Dand L - amino acids in ventricular cerebrospinal fluid from Alzheimer and normal subjects
