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For several years, machine learning approaches have been increasingly investigated in the neuroimaging field to help the diagnosis of dementia. To this end, this work proposes a new pattern recognition technique based on brain parcelling, group selection and tree ensemble algorithms. In addition to prediction performance competitive with more traditional approaches, the method provides easy interpretation...
DaTSCAN is a widely used radiotracer that binds to the dopamine transporters in the striatum and allows us visualizing a possible dopamine deficiency state. Thus, it has been commonly used to assist the diagnosis of Parkinsonism. However, when distinguishing Parkinson's disease (PD) from non-idiopathic parkinsonian variants the usefulness of DaTSCAN is reduced. In these cases, the 18F-Desmethoxyfallypride...
Recently machine learning models have been applied to neuroimaging data, which allow predictions about a variable of interest based on the pattern of activation or anatomy over a set of voxels. These pattern recognition based methods present clear benefits over classical (univariate) techniques, by providing predictions for unseen data, as well as the weights of each feature in the model. Machine...
Positron Emission Tomography (PET) is a noninvasive medical imaging modality that provides information about physiological processes. Due to its ability to measure the brain metabolism, it is widely used to assist the diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD) of Parkinsonism. In order to avoid the subjectivity inherent to the visual exploration of the images, several...
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