Machine Learning: Helping Determine How a Drug Affects the Brain

News   Nov 16, 2017 | Original story from University College London

 
Machine Learning: Helping Determine How a Drug Affects the Brain

Gaze recovery high-dimensional classifier weights. Represented as 3D cubic glyphs varying in colour and scale are the weights of a transductive linear support vector machine classifier trained to relate the high-dimensional pattern of damage to gaze outcome, achieving k-fold cross-validation performance of 78.33% (SE = 1.70%) sensitivity and 82.78% (SE = 0.56%) specificity for distinguishing between patients who recovered from a leftward deviation of gaze and those who did not. Positive weights (dark blue to cyan) favour recovery, negative weights (dark red to yellow) persistence of symptoms. Though hemispheric asymmetry is prominent, note the distribution of weights is highly complex, as one would expect from the complexity of the functional and lesional architectures that generate the critical pattern. Credit: https://doi.org/10.1093/brain/awx288

 
 
 

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