Support vector machine learning-based fMRI data group analysis
By Ze Wang, Anna Rose Childress, Danny J. J. Wang, John A. Detre. 2007
150 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Bilwaj Gaonkar
- Russell T. Shinohara
- Olivier Colliot
- Christos Davatzikos
- Stéphane Lehéricy
- Rémi Cuingnet
- Marie Chupin
- Habib Benali
In Radiology, Nuclear Medicine and Imaging
- Bilwaj Gaonkar
- Russell T. Shinohara
- Charlotte Rosso
- Yves Samson
- Max Welling
- Christos Davatzikos
- Habib Benali
- Rémi Cuingnet
Citations in the corpus
- Interpreting support vector machine models for multivariate group wise analysis in neuroimaging (2015, positive): “SVMs have been widely used in the neuroimaging community to generate diagnostic scores on the basis of brain images Mouro-Miranda et al. (2005) Wang et al. (2007) Cuingnet et al. (2011) Craddock et al. (2009) Fan et al. (2007) Batmanghelich et al. (2012) Vemuri et al. (2008) Davatzikos et al.…”
- Visualizing Deep Neural Network Decisions: Prediction Difference Analysis (2017, methodology): “, 2010), or the p-values of these weights (determined by permutation testing) (Mourao-Miranda et al., 2005; Wang et al., 2007).”
- Analytic estimation of statistical significance maps for support vector machine based multi-variate image analysis and classification (2013, unknown): “…Fan et al., 2007; Klöppel et al., 2008; Koutsouleris et al., 2009; Langs et al., 2011; Mingoia et al., 2012; Mouro-Miranda et al., 2005; Pereira et al., 1998; Richiardi et al., 2011; Sabuncu and Van Leemput, 2011; Vemuri et al., 2008; Venkataraman et al., 2012; Wang et al., 2007; Xu et al., 2009).”
- Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns (2008, unknown): “Without assumptions on this distribution, thresholding might be performed using permutation testing (Mourao-Miranda et al., 2005, Wang et al., 2007).”
- Deriving statistical significance maps for SVM based image classification and group comparisons (2012, methodology): “Hence, replacing univariate methods by multivariate methods such as SVMs [3] [4][5] has been discussed in literature.”
- Spatial regularization of SVM for the detection of diffusion alterations associated with stroke outcome (2011, background): “However , one of the problems with analyzing directly the OMH coefficients is that the corresponding maps are noisy and lack spatial coherence.”