A framework generates synthetic neuroimages with explicit causal control via volumetric ROI changes to produce ground-truth data for benchmarking causal AI in neuroimaging.
V oisey, Tian Xia, Hannah I
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ReTimeCausal is a new EM-based alternating optimization method for causal discovery from irregularly sampled time series that claims consistency guarantees under high missingness.
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A Neuroimaging Simulation Framework for Developing and Evaluating Causal AI
A framework generates synthetic neuroimages with explicit causal control via volumetric ROI changes to produce ground-truth data for benchmarking causal AI in neuroimaging.