<p>For each participant in the re-testing group, the SVM from study 1 was used to distinguish the painful stimuli from the nonpainful stimuli. For each participant in the retesting group, and for their group average, this table displays the SVM's overall accuracy, and positive and negative predictive value (PV). Error is reported as 1 standard deviation. An asterisk indicates performance measures that are significantly greater than chance (<i>p<0.</i>05).</p
<p>Frequency data from occipito-parietal electrodes were used as classification features to separate...
Abstract. We compare two comprehensive classification algorithms, support vec-tor machine (SVM) and ...
<p>Comparison of predictive performances of single feature classes. All values are taken from SVM pr...
<p>Using the activity from six regions of interest (ROIs), SVMs were used to distinguish the painful...
<p>The classifier's performance was assessed at increasing distance thresholds. As the distance thre...
<p>(a) Difference in percentage of trials classified as characteristic of tenderness/affection betwe...
<p>A permutation test was run to determine which brain regions significantly affected the whole-brai...
Background: To understand the neurocognitive effects of brain injury, valid neuropsychological test ...
Pain often exists in the absence of observable injury; therefore, the gold standard for pain assessm...
<p>The volumes and shapes of the hippocampus (Hp) and lateral ventricles (LV) as well as cerebral sp...
***<p>p-value < 0.005,</p>**<p>p-value < 0.01,</p>*<p>p-value < 0.05 at permutation test.</p
Support vector machines (SVMs) constitute one of the most popular and powerful classification method...
<p>The middle column indicates the mean of the accuracy scores for the 10 fold cross validation expe...
<p>The sensitivity, specificity and accuracy of each of three classifiers (Linear SVM, RBF SVM, NN) ...
<div><p>(A) The gray shading indicates prediction accuracy as a function of SVM score (left <i>y</i>...
<p>Frequency data from occipito-parietal electrodes were used as classification features to separate...
Abstract. We compare two comprehensive classification algorithms, support vec-tor machine (SVM) and ...
<p>Comparison of predictive performances of single feature classes. All values are taken from SVM pr...
<p>Using the activity from six regions of interest (ROIs), SVMs were used to distinguish the painful...
<p>The classifier's performance was assessed at increasing distance thresholds. As the distance thre...
<p>(a) Difference in percentage of trials classified as characteristic of tenderness/affection betwe...
<p>A permutation test was run to determine which brain regions significantly affected the whole-brai...
Background: To understand the neurocognitive effects of brain injury, valid neuropsychological test ...
Pain often exists in the absence of observable injury; therefore, the gold standard for pain assessm...
<p>The volumes and shapes of the hippocampus (Hp) and lateral ventricles (LV) as well as cerebral sp...
***<p>p-value < 0.005,</p>**<p>p-value < 0.01,</p>*<p>p-value < 0.05 at permutation test.</p
Support vector machines (SVMs) constitute one of the most popular and powerful classification method...
<p>The middle column indicates the mean of the accuracy scores for the 10 fold cross validation expe...
<p>The sensitivity, specificity and accuracy of each of three classifiers (Linear SVM, RBF SVM, NN) ...
<div><p>(A) The gray shading indicates prediction accuracy as a function of SVM score (left <i>y</i>...
<p>Frequency data from occipito-parietal electrodes were used as classification features to separate...
Abstract. We compare two comprehensive classification algorithms, support vec-tor machine (SVM) and ...
<p>Comparison of predictive performances of single feature classes. All values are taken from SVM pr...