Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph

Information Science, Computer Science, Artificial Intelligence,
Recommendation Systems   Knowledge Graph   Graph Neural Networks   Contextual Information   Biased Random Walk   Recurrent Neural Network   Personalized Preferences  

Knowledge Graph-based Recommendation System: Contextualized Graph Attention Network In recent years, with the explosive growth of online information and content, recommendation systems have become increasingly important in various scenarios such as e-commerce websites and social media platforms. These systems typically aim to provide users with a l...

Knowledge Graph Completion by Jointly Learning Structural Features and Soft Logical Rules

Information Science, Computer Science, Artificial Intelligence,
knowledge graph completion   knowledge graph embedding   graph attention neural networks   link prediction   soft logical rules  

In recent years, Knowledge Graphs (KG) have been widely used in many artificial intelligence tasks. Knowledge graphs represent entities and their relationships using triplets consisting of a head entity, a relation, and a tail entity. For example, the triplet (h = Paris, r = capital_of, t = France) represents a common-sense fact about the real worl...

Deep Relational Graph Infomax for Knowledge Graph Completion

Information Science, Computer Science, Artificial Intelligence,
knowledge graph embedding   mutual information maximization   graph attention networks   knowledge graph completion   artificial intelligence  

Knowledge Graph (KG) embedding technology is an important research topic in the field of artificial intelligence, mainly used for knowledge acquisition and extension of knowledge graphs. In recent years, although many graph embedding methods have been proposed, these methods typically focus only on the semantic information of the knowledge graph, i...

Graph-based Conditional Generative Adversarial Networks for Major Depressive Disorder Diagnosis with Synthetic Functional Brain Network Generation

Graph-based Conditional Generative Adversarial Networks for Major Depressive Disorder Diagnosis with Synthetic Functional Brain Network Generation

Information Science, Artificial Intelligence, Medicine, Psychiatry, Neurology, Medical Imaging,
Major Depressive Disorder   Generative Adversarial Networks   Graph Convolutional Networks   Resting-State Functional MRI   Synthetic Functional Connectivity  

Graph-Based Conditional Generative Adversarial Network for Generating Synthetic Functional Brain Networks to Diagnose Major Depressive Disorder Research Background: Major Depressive Disorder (MDD) is a widespread mental disorder that affects millions of people’s lives and poses a significant threat to global health. Studies have shown that function...

Distinguishing Parkinsonian Rest Tremor from Voluntary Hand Movements through Subthalamic and Cortical Activity

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Life Sciences, Biophysics,
Parkinson’s disease   rest tremor   voluntary hand movements   brain activity   subthalamic nucleus   machine learning  

Parkinson’s disease (PD) is a common neurodegenerative disorder characterized mainly by resting tremor, bradykinesia, and rigidity. Deep Brain Stimulation (DBS) has been widely used to treat the motor symptoms of PD (Krauss et al., 2021). However, DBS treatment also has significant side effects, most of which are caused by the extension of stimulat...

Early Prediction of Drug-Resistant Epilepsy Using Clinical and EEG Features Based on Convolutional Neural Network

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging,
Drug-resistant epilepsy   Antiseizure medication   Electroencephalogram   Convolutional neural network   Machine learning  

Research Background and Purpose Epilepsy is a spontaneous and severe neurological disorder characterized by recurrent seizures, affecting approximately 50 million people worldwide [1]. Despite recent advances in anti-seizure medications (ASMs), drug-resistant epilepsy (DRE) still affects 20% to 30% of epilepsy patients [1-3]. DRE patients face sign...