AI Medical Compendium Topic:
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Comparing feedforward and recurrent neural network architectures with human behavior in artificial grammar learning.

Scientific reports
In recent years artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language processing, have witnessed remarkable improvements in state of the art ...

Continuous Similarity Learning with Shared Neural Semantic Representation for Joint Event Detection and Evolution.

Computational intelligence and neuroscience
In the era of the rapid development of today's Internet, people often feel overwhelmed by vast official news streams or unofficial self-media tweets. To help people obtain the news topics they care about, there is a growing need for systems that can ...

Transforming task representations to perform novel tasks.

Proceedings of the National Academy of Sciences of the United States of America
An important aspect of intelligence is the ability to adapt to a novel task without any direct experience (zero shot), based on its relationship to previous tasks. Humans can exhibit this cognitive flexibility. By contrast, models that achieve superh...

Artificial intelligence: Thinking outside the box.

Best practice & research. Clinical gastroenterology
Artificial intelligence (AI) for luminal gastrointestinal endoscopy is rapidly evolving. To date, most applications have focused on colon polyp detection and characterization. However, the potential of AI to revolutionize our current practice in endo...

A Novel Neural Model With Lateral Interaction for Learning Tasks.

Neural computation
We propose a novel neural model with lateral interaction for learning tasks. The model consists of two functional fields: an elementary field to extract features and a high-level field to store and recognize patterns. Each field is composed of some n...

A Brain-Inspired Framework for Evolutionary Artificial General Intelligence.

IEEE transactions on neural networks and learning systems
From the medical field to agriculture, from energy to transportation, every industry is going through a revolution by embracing artificial intelligence (AI); nevertheless, AI is still in its infancy. Inspired by the evolution of the human brain, this...

A User-Oriented Intelligent Access Selection Algorithm in Heterogeneous Wireless Networks.

Computational intelligence and neuroscience
A heterogeneous wireless network (HWN) contains many kinds of wireless networks with overlapping areas of signal coverage. One of the research topics on HWNs is how to make users choose the most suitable network. This paper designs a user-oriented in...

A modeling framework for adaptive lifelong learning with transfer and savings through gating in the prefrontal cortex.

Proceedings of the National Academy of Sciences of the United States of America
The prefrontal cortex encodes and stores numerous, often disparate, schemas and flexibly switches between them. Recent research on artificial neural networks trained by reinforcement learning has made it possible to model fundamental processes underl...

Embracing Change: Continual Learning in Deep Neural Networks.

Trends in cognitive sciences
Artificial intelligence research has seen enormous progress over the past few decades, but it predominantly relies on fixed datasets and stationary environments. Continual learning is an increasingly relevant area of study that asks how artificial sy...

A recurrent neural network framework for flexible and adaptive decision making based on sequence learning.

PLoS computational biology
The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. This is anal...