AIMC Topic: Humans

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A simple interpretation of undirected edges in essential graphs is wrong.

PloS one
Artificial intelligence for causal discovery frequently uses Markov equivalence classes of directed acyclic graphs, graphically represented as essential graphs, as a way of representing uncertainty in causal directionality. There has been confusion r...

Designing Interpretable Recurrent Neural Networks for Video Reconstruction via Deep Unfolding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Deep unfolding methods design deep neural networks as learned variations of optimization algorithms through the unrolling of their iterations. These networks have been shown to achieve faster convergence and higher accuracy than the original optimiza...

Optimal Bayesian Transfer Learning for Count Data.

IEEE/ACM transactions on computational biology and bioinformatics
There is often a limited amount of omics data to design predictive models in biomedicine. Knowing that these omics data come from underlying processes that may share common pathways and disease mechanisms, it may be beneficial for designing a more ac...

Unbiased Recursive Partitioning Enables Robust and Reliable Outcome Prediction in Acute Spinal Cord Injury.

Journal of neurotrauma
Neurological disorders usually present very heterogeneous recovery patterns. Nonetheless, accurate prediction of future clinical end-points and robust definition of homogeneous cohorts are necessary for scientific investigation and targeted care. For...

Robotic rehabilitation for end-effector device and botulinum toxin in upper limb rehabilitation in chronic post-stroke patients: an integrated rehabilitative approach.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Determine the effects of an integrated rehabilitation protocol, including botulinum toxin and conventional rehabilitation exercise plus end-effector (EE) robotic training for functional recovery of the upper limb (UL) compared to training...

Machine learning-based decision tree classifier for the diagnosis of progressive supranuclear palsy and corticobasal degeneration.

Neuropathology and applied neurobiology
AIMS: This study aimed to clarify the different topographical distribution of tau pathology between progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) and establish a machine learning-based decision tree classifier.

Analysis of the human connectome data supports the notion of a "Common Model of Cognition" for human and human-like intelligence across domains.

NeuroImage
The Common Model of Cognition (CMC) is a recently proposed, consensus architecture intended to capture decades of progress in cognitive science on modeling human and human-like intelligence. Because of the broad agreement around it and preliminary ma...