AI Medical Compendium Topic

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Evaluating a Semiautonomous Brain-Computer Interface Based on Conformal Geometric Algebra and Artificial Vision.

Computational intelligence and neuroscience
In this paper, we evaluate a semiautonomous brain-computer interface (BCI) for manipulation tasks. In such a system, the user controls a robotic arm through motor imagery commands. In traditional process-control BCI systems, the user has to provide t...

Kinematic Redundancy Analysis during Goal-Directed Motion for Trajectory Planning of an Upper-Limb Exoskeleton Robot.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The kinematic redundancy of human arm imposes challenges on joint space trajectory planning for upper-limb rehabilitation robot. This paper aims to investigate normal motion patterns in reaching and reach-to-grasp movements, and obtain the unique sol...

How to achieve trustworthy artificial intelligence for health.

Bulletin of the World Health Organization
Artificial intelligence holds great promise in terms of beneficial, accurate and effective preventive and curative interventions. At the same time, there is also awareness of potential risks and harm that may be caused by unregulated developments of ...

Can exascale computing and explainable artificial intelligence applied to plant biology deliver on the United Nations sustainable development goals?

Current opinion in biotechnology
Human population growth and accelerated climate change necessitate agricultural improvements using designer crop ideotypes (idealized plants that can grow in niche environments). Diverse and highly skilled research groups must integrate efforts to br...

Neuromodulated attention and goal-driven perception in uncertain domains.

Neural networks : the official journal of the International Neural Network Society
In uncertain domains, the goals are often unknown and need to be predicted by the organism or system. In this paper, contrastive Excitation Backprop (c-EB) was used in two goal-driven perception tasks - one with pairs of noisy MNIST digits and the ot...

Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control.

Communications biology
Efficient action control is indispensable for goal-directed behaviour. Different theories have stressed the importance of either attention or response selection sub-processes for action control. Yet, it is unclear to what extent these processes can b...

Graph Convolution Networks with manifold regularization for semi-supervised learning.

Neural networks : the official journal of the International Neural Network Society
In recent times, Graph Convolution Networks (GCN) have been proposed as a powerful tool for graph-based semi-supervised learning. In this paper, we introduce a model that enhances label propagation of Graph Convolution Networks (GCN). More precisely,...

Generative Adversarial Networks are special cases of Artificial Curiosity (1990) and also closely related to Predictability Minimization (1991).

Neural networks : the official journal of the International Neural Network Society
I review unsupervised or self-supervised neural networks playing minimax games in game-theoretic settings: (i) Artificial Curiosity (AC, 1990) is based on two such networks. One network learns to generate a probability distribution over outputs, the ...

Computational Goals, Values and Decision-Making.

Science and engineering ethics
Considering the popular framing of an artificial intelligence as a rational agent that always seeks to maximise its expected utility, referred to as its goal, one of the features attributed to such rational agents is that they will never select an ac...