The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods

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2. Altered bile acid profile in mild cognitive impairment and Alzheimer's disease: Relationship to neuroimaging and CSF biomarkers
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3. Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging
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4. Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates
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5. Graph Neural Networks in Network Neuroscience
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6. A biological classification of Huntington's disease: the Integrated Staging System
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7. 2014 Update of the Alzheimer’s Disease Neuroimaging Initiative: A review of papers published since its inception
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8. Dysfunctionally phosphorylated type 1 insulin receptor substrate in neural‐derived blood exosomes of preclinical Alzheimer's disease
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9. Benchmarking functional connectome-based predictive models for resting-state fMRI
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10. Biomarkers of neurodegeneration for diagnosis and monitoring therapeutics
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11. Abnormal connectivity in the posterior cingulate and hippocampus in early Alzheimer's disease and mild cognitive impairment
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12. Fully automatic hippocampus segmentation and classification in Alzheimer's disease and mild cognitive impairment applied on data from ADNI
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13. Deep ensemble learning of sparse regression models for brain disease diagnosis
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14. Basal forebrain degeneration precedes and predicts the cortical spread of Alzheimer’s pathology
    Taylor W. Schmitz, R. Nathan Spreng, The Alzheimer's Disease Neuroimaging Initiative, Michael Walter Weiner, Paul S. S Aisen, Ronald Carl Petersen, Clifford R. Jack, William J. Jagust, John Q. Trojanowki, Arthur W. Toga et al. · 2016 · Nature Communications
15. Alzheimer Disease: Quantitative Structural Neuroimaging for Detection and Prediction of Clinical and Structural Changes in Mild Cognitive Impairment
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16. Gray matter reduction associated with systemic chemotherapy for breast cancer: a prospective MRI study
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17. DeepAD: Alzheimer’s Disease Classification via Deep Convolutional Neural Networks using MRI and fMRI
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18. Machine Learning Techniques for the Diagnosis of Alzheimer’s Disease
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19. Ferritin levels in the cerebrospinal fluid predict Alzheimer’s disease outcomes and are regulated by APOE
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20. A deep CNN based multi-class classification of Alzheimer's disease using MRI
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21. A Phase II Study of Fornix Deep Brain Stimulation in Mild Alzheimer’s Disease
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22. The essential elements of Alzheimer’s disease
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23. Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data
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24. Mapping anterior temporal lobe language areas with fMRI: a multicenter normative study
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25. Mouse models of Alzheimer's disease
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26. NPTX2 and cognitive dysfunction in Alzheimer’s Disease
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27. Ensemble sparse classification of Alzheimer's disease
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28. Hubs of brain functional networks are radically reorganized in comatose patients
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29. A data-driven model of biomarker changes in sporadic Alzheimer’s disease
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30. MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection
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31. Update on the biomarker core of the Alzheimer's Disease Neuroimaging Initiative subjects
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32. Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis
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33. Brain development and aging: Overlapping and unique patterns of change
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34. Random Forest ensembles for detection and prediction of Alzheimer's disease with a good between-cohort robustness
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35. Deviant processing of letters and speech sounds as proximate cause of reading failure: A functional magnetic resonance imaging study of dyslexic children.
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36. Symmetric Diffeomorphic Modeling of Longitudinal Structural MRI
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37. Distinct anatomical subtypes of the behavioural variant of frontotemporal dementia: a cluster analysis study
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38. A new switching-delayed-PSO-based optimized SVM algorithm for diagnosis of Alzheimer’s disease
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39. Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project
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40. Cerebrospinal fluid neurogranin: relation to cognition and neurodegeneration in Alzheimer’s disease
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41. The Alzheimer's Disease Neuroimaging Initiative 2 PET Core: 2015
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42. Multi-parametric neuroimaging reproducibility: A 3-T resource study
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43. Type 2 diabetes mellitus and biomarkers of neurodegeneration
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44. Detection of cortical thickness correlates of cognitive performance: Reliability across MRI scan sessions, scanners, and field strengths
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45. Cerebrospinal fluid tau, neurogranin, and neurofilament light in Alzheimer's disease
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46. From estimating activation locality to predicting disorder: a review of pattern recognition for neuroimaging-based psychiatric diagnostics
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48. Diagnosis of Alzheimer’s Disease via Multi-Modality 3D Convolutional Neural Network
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49. Amyloid and APOE ε4 interact to influence short-term decline in preclinical Alzheimer disease
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50. A Transfer Learning Approach for Early Diagnosis of Alzheimer’s Disease on MRI Images
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51. The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository
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52. Multi-Method Analysis of MRI Images in Early Diagnostics of Alzheimer's Disease
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53. Diagnostic neuroimaging across diseases
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54. Pain attenuation through mindfulness is associated with decreased cognitive control and increased sensory processing in the brain
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55. Longitudinal MRI atrophy biomarkers: Relationship to conversion in the ADNI cohort
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56. Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
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57. Deep learning based synthesis of MRI, CT and PET: Review and analysis
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58. Voxelwise genome-wide association study (vGWAS)
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59. Effective feature learning and fusion of multimodality data using stage‐wise deep neural network for dementia diagnosis
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60. QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
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61. What is a representative brain? Neuroscience meets population science
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62. Periodontal disease associates with higher brain amyloid load in normal elderly
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63. Structural Imaging Measures of Brain Aging
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64. Multimodal imaging in Alzheimer's disease: validity and usefulness for early detection
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65. Methods and considerations for longitudinal structural brain imaging analysis across development
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66. Mild cognitive impairment due to Alzheimer disease in the community
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67. Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach
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68. Data sharing in neuroimaging research
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69. A Survey on Incomplete Multiview Clustering
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70. Brain aging mechanisms with mechanical manifestations
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71. Exercise and probiotics attenuate the development of Alzheimer's disease in transgenic mice: Role of microbiome
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72. Deep reinforcement learning in computer vision: a comprehensive survey
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73. Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA
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74. Multi-Atlas Skull-Stripping
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75. Predicting clinical scores from magnetic resonance scans in Alzheimer's disease
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76. Ensemble of 3D densely connected convolutional network for diagnosis of mild cognitive impairment and Alzheimer’s disease
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77. Functional Impairment in Elderly Patients With Mild Cognitive Impairment and Mild Alzheimer Disease<alt-title>Impairment in MCI and AD Patients</alt-title>
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78. MGH–USC Human Connectome Project datasets with ultra-high b-value diffusion MRI
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79. Classification of Alzheimer’s Disease by Combination of Convolutional and Recurrent Neural Networks Using FDG-PET Images
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80. Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative
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81. Partial volume correction in quantitative amyloid imaging
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82. Biomedical text mining and its applications in cancer research
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83. Automated cross-sectional and longitudinal hippocampal volume measurement in mild cognitive impairment and Alzheimer's disease
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84. Brain tumor segmentation using K‐means clustering and deep learning with synthetic data augmentation for classification
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85. Alzheimer's disease biomarker discovery using SOMAscan multiplexed protein technology
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86. MRI and CSF biomarkers in normal, MCI, and AD subjects
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87. The Disconnected Brain and Executive Function Decline in Aging
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88. RNN-based longitudinal analysis for diagnosis of Alzheimer’s disease
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89. Independent information from cerebrospinal fluid amyloid-β and florbetapir imaging in Alzheimer's disease
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90. High‐order resting‐state functional connectivity network for MCI classification
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91. Inter-modality relationship constrained multi-modality multi-task feature selection for Alzheimer's Disease and mild cognitive impairment identification
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92. Automated mapping of hippocampal atrophy in 1-year repeat MRI data from 490 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls
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93. A commonly carried allele of the obesity-related FTO gene is associated with reduced brain volume in the healthy elderly
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94. Emerging Applications of Artificial Intelligence in Neuro-Oncology
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95. SUMA
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96. Impact of the Alzheimer's Disease Neuroimaging Initiative, 2004 to 2014
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97. MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults
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98. Identifying patients with Alzheimer’s disease using resting-state fMRI and graph theory
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99. Brain imaging of neurovascular dysfunction in Alzheimer’s disease
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100. Tau, amyloid, and cascading network failure across the Alzheimer's disease spectrum
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