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In Huntington's disease (HD), accurate estimates of expected future motor impairments are key for clinical trials. Individual prognosis is only partially explained by genetics. However, studies so far have focused on predicting the time to clinical diagnosis based on fixed impairment levels, as opposed to predicting impairment in time windows comparable to the duration of a clinical trial. Here we...
The objective of this paper is to further validate theoretically and empirically a nonlinear independent component analysis (ICA) algorithm implemented with a deep learning architecture. We first revisited its formulation to verify its consistency with the criterion of minimization of mutual information. Then, we applied the nonlinear independent component estimation algorithm (NICE) to synthetic...
Deep learning methods have significantly improved classification accuracy in different areas such as speech, object and text recognition. However, this field has only began to be explored in the brain imaging field, which differs from other fields in terms of the amount of data available, its data dimensionality and other factors. This paper proposes a methodology to generate an extensive synthetic...
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