Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) Found by Hierarchical Clustering

Table 1

Methods and key findings of cited literature.

Reference	MCI or AD	Method	Application
[5]	MCI	Multilayer clustering	Identification of rapid and slow decliners
[11]	AD	Visual rating scales	Recognizing AD subtypes
[12]	AD	Random forest pairwise similarity and hierarchical clustering	Varying rates of degeneration of AD subtypes
[7]	AD	-means clustering and support vector machines	Subtypes of AD atrophy
[18]	MCI and AD	Voxel-wise statistical analysis and regression models	Brain atrophy w.r.t age and APOE genotype
[14]	AD	Voxel-based morphometry, statistical analysis using ANOVA	Regional atrophy patterns and progression rates of AD subtypes
[16]	AD	Neurofibrillary tangle count using digital microscopy, statistical methods (ANOVA, -tests)	Subtypes of AD and distinct clinical characteristics
[17]	AD	Cortical, hippocampal volume measurements, statistical methods	Progression rates of AD subtypes
[21]	MCI and AD	Voxel-based morphometry	Atrophy pattern related to progression from MCI to AD
[19]	MCI and AD	Semisupervised machine learning and random forest classification	Predicting conversion from MCI to AD
[22]	AD	Voxel-based morphometry and regression analysis	Precuneus atrophy in early-onset Alzheimer’s disease