Abstract:
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There have been major advances in the statistical analysis of neuroimaging data over the last two decades. Yet, due to inherent complexities and the massive dimensionality of the data, many needs remain for novel statistical development. There are still enormous opportunities for neuroimaging to affect science and medicine, for instance as a key tool for precision medicine. However, these potential advances depend heavily on statistics for the ability to establish sound estimation, inference, and prediction frameworks. We will briefly discuss existing approaches to analyze neuroimaging data and highlight remaining challenges and opportunities. Among other topics, this roundtable will address prediction methods, Bayesian modeling, functional brain networks, the search for neuroimaging biomarkers, and multimodal imaging.
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