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Disruption of Functional Brain Networks in Alzheimer's Disease: What Can We Learn from Graph Spectral Analysis of Resting-State Magnetoencephalography?, , , , , and . Brain Connect., 2 (2): 45-55 (2012)Microglial activation in healthy aging., , , , , , , , , and 1 other author(s). NeuroImage, 52 (Supplement-1): S32 (2010)Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease., , , , , , , , , and 7 other author(s). CoRR, (2020)Single-Subject Gray Matter Graph Properties and Their Relationship with Cognitive Impairment in Early- and Late-Onset Alzheimer's Disease., , , , , , , , and . Brain Connect., 4 (5): 337-346 (2014)Prior-knowledge-informed deep learning for lacune detection and quantification using multi-site brain MRI., , , , , , , and . CoRR, (2023)Decreased P-glycoprotein function at the blood-brain barrier in patients with Alzheimer's disease as shown by (R)-11Cverapamil and PET., , , , , , , , , and . NeuroImage, 52 (Supplement-1): S53 (2010)Identifying a task-invariant cognitive reserve network using task potency., , , , and . NeuroImage, (2020)An Interpretable Machine Learning Model with Deep Learning-Based Imaging Biomarkers for Diagnosis of Alzheimer's Disease., , , , , , , , , and 2 other author(s). ISIC/Care-AI/MedAGI/DeCaF@MICCAI, volume 14393 of Lecture Notes in Computer Science, page 69-78. Springer, (2023)Pseudo-healthy Image Synthesis for White Matter Lesion Segmentation., , , , , , , , , and 8 other author(s). SASHIMI@MICCAI, volume 9968 of Lecture Notes in Computer Science, page 87-96. (2016)Increased microglial activation in MCI and AD: An (R)-11CPK11195 PET study., , , , , , , , , and 2 other author(s). NeuroImage, 52 (Supplement-1): S146 (2010)