Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imaging.

By Christos Davatzikos, Yong Fan, Xiaoying Wu, Dinggang Shen, Susan M. Resnick. Neurobiology of Aging, 2008

403 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Physiology, Psychiatry and Mental health

View Paper: https://www.semanticscholar.org/paper/52bb7c5d679b75b0e4cd980274c931c0ac65fb90

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Citations in the corpus

A review on neuroimaging‐based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages (2017, positive): “…automated methods, various ranking-based methods, such as t- tests (Tang et al., 2016; Wee et al., 2013) and Pearson's correlation coefficient test (Davatzikos et al., 2008; Wee et al., 2011), wrapperbased methods, a combination of ranking and wrapper-based methods, such as mRMR (Wee et al.,…”
Investigating the predictive value of whole-brain structural MR scans in autism: A pattern classification approach (2010, background): “Such approaches are thus designed to describemean differences at the voxel-level rather than to make a prediction (e.g., group affiliation/separation; Davatzikos et al., 2008).”
Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge (2015, methodology): “…used, which is a common practice in studies of computer-aided diagnosis methods (Cuingnet et al., 2011; Klöppel et al., 2008; Falahati et al., 2014; Davatzikos et al., 2008a; Duchesne et al., 2008; Fan et al., 2008a,b; Gray et al., 2013; Koikkalainen et al., 2012; Magnin et al., 2009; Vemuri et…”
Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease (2009, neutral): “…accuracies presented here are comparable to one prior PET study utilizing a radioactive amyloid and tau protein tracer (Small et al ., 2006) and two prior MRI studies where a smaller number of subjects were examined from a single cohort (Killiany et al ., 2000; Davatzikos et al ., 2008).”
Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging (2009, positive): “The disease severity of our AD and MCI patients was similar to those included in Fan et al. (2008) (mean MMS=23 for AD and 27 for MCI) and in Davatzikos et al. (2008a) (mean MMS=26 for MCI).”
Deep ensemble learning of sparse regression models for brain disease diagnosis (2017, background): “However, it was limited to analyze the high dimensional neuroimaging data until the application of machine learning techniques, which are now playing core roles in the field (Davatzikos et al., 2008).”
Prediction of MCI to AD conversion, via MRI, CSF biomarkers, pattern classification (2010, positive): “…recent studies have suggested that early changes of the SPARE-AD scores and other morphological measurements, as well as CSF biomarkers, in cognitively normal elderly are good predictors of future progression to MCI (Davatzikos et al., 2008a, 2008b, 2009; Driscoll et al., 2009; Fagan et al., 2009).”
Structural and functional biomarkers of prodromal Alzheimer's disease: A high-dimensional pattern classification study (2008, methodology): “…Golland et al., 2002; Lao et al., 2004; Liu et al., 2004; Timoner et al., 2002), and have shown great potential in a variety of neuroimaging studies (Davatzikos et al., 2008, 2005a,b; Fan et al., 2008a, 2005, 2006b, 2007b, Kawasaki et al., 2007; Mourao-Miranda et al., 2005; Yoon et al., 2007).”
Machine Learning and Radiology (2012, methodology): “developed an automatic method to detect these patterns via high-dimensional image warping, robust feature extraction, and SVM (Davatzikos et al., 2008; Fan et al., 2005).”
Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: Exploring the influence of various parameters (2010, neutral): “…explored and subsequently a variety of classi ﬁ cation methods have been employed to separate one or more groups of patients from healthy controls (Davatzikos et al., 2005, 2008a, 2008b; Fan et al., 2008a, 2008b; Klöppel et al., 2008a, 2008b, 2009; Liu et al., 2004; Teipel et al., 2007; Vemuri…”
Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease (2010, methodology): “Recently, such multivariate methods have been adopted for the analysis of structural MRI to detect spatial patterns of atrophy in AD (Chen and Herskovits, 2006; Davatzikos et al., 2008; DeCarli et al., 1995; Duchesne et al., 2008a,b, 2009; Fan et al., 2008; Kloeppel et al., 2008; Misra et al., 2009;”
Automatic classification of patients with Alzheimer's disease from structural MRI: A comparison of ten methods using the ADNI database (2011, methodology): “Davatzikos et al. (2008b) and Fan et al.”
Ensemble Sparse Classification of Alzheimer’s Disease (2012, methodology): “…feature selection is another important technique for dimensionality reduction which selects the most discriminative features and at the same time eliminates the redundant features (Davatzikos et al., 2006, epub; Davatzikos et al., 2008; Fan et al., 2005a; Vemuri et al., 2008; Yoon et al., 2007).”