AIMC Topic: Humans

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PrediRep: Modeling hierarchical predictive coding with an unsupervised deep learning network.

Neural networks : the official journal of the International Neural Network Society
Hierarchical predictive coding (hPC) provides a compelling framework for understanding how the cortex predicts future sensory inputs by minimizing prediction errors through an internal generative model of the external world. Existing deep learning mo...

Augmenting interaction effects in convolutional networks with taylor polynomial gated units.

Neural networks : the official journal of the International Neural Network Society
Transformer-based vision models are often assumed to have an advantage over traditional convolutional neural networks (CNNs) due to their ability to model long-range dependencies and interactions between inputs. However, the remarkable success of pur...

SH: Long-tailed classification via spatial constraint sampling, scalable network, and hybrid task.

Neural networks : the official journal of the International Neural Network Society
Long-tailed classification is a significant yet challenging vision task that aims to making the clearest decision boundaries via integrating semantic consistency and texture characteristics. Unlike prior methods, we design spatial constraint sampling...

Incremental model-based reinforcement learning with model constraint.

Neural networks : the official journal of the International Neural Network Society
In model-based reinforcement learning (RL) approaches, the estimated model of a real environment is learned with limited data and then utilized for policy optimization. As a result, the policy optimization process in model-based RL is influenced by b...

Ultrasonic-Based Radiomics Signature With Machine Learning for Differentiating Prognostic Subsets of Pediatric Peripheral Neuroblastic Tumors: A Retrospective Study.

Ultrasound in medicine & biology
OBJECTIVE: To construct and select a better model based on ultrasonic-based radiomics features and clinical characteristics for prognostic subsets of pediatric neuroblastic tumors.

Towards a latent space cartography of subjective experience in mental health.

Psychiatry and clinical neurosciences
AIMS: The way that individuals subjectively experience the world greatly influences their own mental well-being. However, it remains a considerable challenge to precisely characterize the breadth and depth of such experiences. One persistent problem ...

Using Artificial Intelligence to Advance Eating Disorder Research, Treatment and Practice.

The International journal of eating disorders
Artificial intelligence (AI) has the potential to revolutionize eating disorder research, treatment, and practice by assisting with complex problems such as predicting illness prognosis, supporting diagnostic decisions, tailoring treatment plans, and...

Virtual torque control combining with modal decoupling research for hydraulic-driven lower limb exoskeleton robot.

ISA transactions
The hydraulic-driven lower limb exoskeleton robot (HDLLER) can provide excellent assistance during human walking. However, complex torque coupling disturbances exist between each joint, negatively impacting the precise torque tracking of each joint c...

Geometric deep learning with adaptive full-band spatial diffusion for accurate, efficient, and robust cortical parcellation.

Medical image analysis
Cortical parcellation delineates the cerebral cortex into distinct regions according to their distinctiveness in anatomy and/or function, which is a fundamental preprocess in brain cortex analysis and can influence the accuracy and specificity of sub...

EEGConvNeXt: A novel convolutional neural network model for automated detection of Alzheimer's Disease and Frontotemporal Dementia using EEG signals.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep learning models have gained widespread adoption in healthcare for accurate diagnosis through the analysis of brain signals. Neurodegenerative disorders like Alzheimer's Disease (AD) and Frontotemporal Dementia (FD) are ...