AIMC Topic: Computer Graphics

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Bind: large-scale biological interaction network discovery through knowledge graph-driven machine learning.

Journal of translational medicine
BACKGROUND: Biological systems derive from complex interactions between entities ranging from biomolecules to macroscopic structures, forming intricate networks essential for understanding disease mechanisms and developing therapeutic interventions. ...

Advancing ADMET prediction for major CYP450 isoforms: graph-based models, limitations, and future directions.

Biomedical engineering online
Understanding Cytochrome P450 (CYP) enzyme-mediated metabolism is critical for accurate Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) predictions, which play a pivotal role in drug discovery. Traditional approaches, while foun...

Enhancing online interaction through avatar-based dialogue systems utilizing the approaching movement.

PloS one
The rise in online interactions has introduced multiple challenges, including confusion during virtual meetings and fatigue associated with prolonged video conferencing. To address these issues, this study advocates using computer graphics (CG) avata...

BHGNN-RT: Capturing bidirectionality and network heterogeneity in graphs.

PloS one
Graph neural networks (GNNs) have shown great promise for representation learning on complex graph-structured data, but existing models often fall short when applied to directed heterogeneous graphs. In this study, we proposed a novel embedding metho...

TempODEGraphNet: predicting user churn using dynamic social graphs and neural ODEs.

PloS one
Research on user churn prediction has been conducted across various domains for a long time. Among these, the gaming domain is characterized by its potential for diverse types of interactions between users. Due to this characteristic, many studies on...

SensARy Substitution: Augmented Reality Techniques to Enhance Force Perception in Touchless Robot Control.

IEEE transactions on visualization and computer graphics
The lack of haptic feedback in touchless human-robot interaction is critical in applications such as robotic ultrasound, where force perception is crucial to ensure image quality. Augmented reality (AR) is a promising tool to address this limitation ...

FovealNet: Advancing AI-Driven Gaze Tracking Solutions for Efficient Foveated Rendering in Virtual Reality.

IEEE transactions on visualization and computer graphics
Leveraging real-time eye tracking, foveated rendering optimizes hardware efficiency and enhances visual quality virtual reality (VR). This approach leverages eye-tracking techniques to determine where the user is looking, allowing the system to rende...

Hit Around: Substitutional Moving Robot for Immersive and Exertion Interaction with Encountered-Type Haptic.

IEEE transactions on visualization and computer graphics
Previous works have shown the potential of immersive technologies to make physical activities a more engaging experience. With encountered-type haptic feedback, users can perceive a more realistic sensation for exertion interaction in substitutions r...

Enhancing Patient Acceptance of Robotic Ultrasound through Conversational Virtual Agent and Immersive Visualizations.

IEEE transactions on visualization and computer graphics
Robotic ultrasound systems have the potential to improve medical diagnostics, but patient acceptance remains a key challenge. To address this, we propose a novel system that combines an AI-based virtual agent, powered by a large language model (LLM),...

Pair-wise or high-order? A self-adaptive graph framework for knowledge graph embedding.

Neural networks : the official journal of the International Neural Network Society
Knowledge graphs (KGs) depict entities as nodes and connections as edges, and they are extensively utilized in numerous artificial intelligence applications. However, knowledge graphs often suffer from incompleteness, which seriously affects downstre...