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Longitudinal brain structure changes in Parkinson's disease: A replication study

Author(s): Sokolowski A; Bhagwat N; Chatelain Y; Dugré M; Hanganu A; Monchi O; McPherson B; Wang M; Poline JB; Sharp M; Glatard T;

Context: An existing major challenge in Parkinson's disease (PD) research is the identification of biomarkers of disease progression. While magnetic resonance imaging is a potential source of PD biomarkers, none of the magnetic resonance imaging measures of PD are robust enough to warrant the ...

Article GUID: 38295031


Numerical stability of DeepGOPlus inference

Author(s): Gonzalez Pepe I; Chatelain Y; Kiar G; Glatard T;

Convolutional neural networks (CNNs) are currently among the most widely-used deep neural network (DNN) architectures available and achieve state-of-the-art performance for many problems. Originally applied to computer vision tasks, CNNs work well with any data with a spatial relationship, besides images, and have been applied to different fields. However ...

Article GUID: 38285635


Numerical uncertainty in analytical pipelines lead to impactful variability in brain networks

Author(s): Kiar G; Chatelain Y; de Oliveira Castro P; Petit E; Rokem A; Varoquaux G; Misic B; Evans AC; Glatard T;

The analysis of brain-imaging data requires complex processing pipelines to support findings on brain function or pathologies. Recent work has shown that variability in analytical decisions, small amounts of noise, or computational environments can lead to substantial differences in the results, ...

Article GUID: 34724000


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