Self-Attention Similarity Guided Graph Convolutional Network for Multi-type Lower-Grade Glioma Classification Research

Self-Attention Similarity Guided Graph Convolutional Network for Multi-type Lower-Grade Glioma Classification Research

Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Oncology,
low-grade glioma   brain tumor classification   3D brain MRI   graph convolutional network   self-attention  

Graph Convolutional Network Based on Self-Attention Similarity for Multi-type Low-Grade Glioma Classification 1. Research Background Low-grade glioma is a common malignant brain tumor caused by the cancerous transformation of glial cells in the brain and spinal cord. Gliomas are characterized by high incidence, high recurrence rate, high mortality ...

CaNet: Context Aware Network for Brain Glioma Segmentation

CaNet: Context Aware Network for Brain Glioma Segmentation

Information Science, Computer Science, Medicine, Neurology, Neurosurgery, Medical Imaging, Oncology, Life Sciences, Immunology,
brain glioma   conditional random field   graph convolutional network   image segmentation  

Context-Aware Network Study Report for Glioma Segmentation Glioma is a common type of adult brain tumor that severely harms health and has a high mortality rate. To provide sufficient evidence for early diagnosis, surgical planning, and postoperative observation, multimodal Magnetic Resonance Imaging (MRI) has been widely applied in this field. The...

Deep-Learning-Based Motor Imagery EEG Classification by Exploiting the Functional Connectivity of Cortical Source Imaging

Information Science, Electronic Information, Automation, Artificial Intelligence, Medicine, Neurology, Medical Imaging,
deep learning   motor imagery EEG   cortical source imaging   brain functional connectivity   spatiotemporal features   graph convolutional network  

Deep-learning-based Motor Imagery EEG Classification by Exploiting the Functional Connectivity of Cortical Source Imaging Research Background and Motivation A brain-computer interface (BCI) is a system that directly decodes and outputs brain activity information without relying on related neural pathways and muscles, thereby achieving communication...

Identification of Autism Spectrum Disorder Using Multiple Functional Connectivity-Based Graph Convolutional Network

Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Clinical Psychology, Medical Imaging,
autism spectrum disorder   graph convolutional network   functional connectivity   brain network   readout layer  

The title of this paper is “Identification of Autism Spectrum Disorder Using Multiple Functional Connectivity-based Graph Convolutional Network,” published in the journal “Medical & Biological Engineering & Computing,” volume 62, pages 2133-2144, in 2024. This paper proposes a multiple functional connectivity-based graph convolutional network (mfc-...

Predicting Drug-Target Affinity by Learning Protein Knowledge from Biological Networks

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering, Biophysics,
drug-target affinity   variational graph autoencoders   graph convolutional network   protein-protein interaction  

Predicting Drug-Target Affinity Based on Learning Protein Knowledge from Biological Networks Background The prediction of drug-target affinity (DTA) plays a crucial role in drug discovery. Efficient and accurate DTA prediction can significantly reduce the time and economic costs of new drug development. In recent years, the explosive development of...

Attention-Guided Graph Structure Learning Network for EEG-enabled Auditory Attention Detection

Attention-Guided Graph Structure Learning Network for EEG-enabled Auditory Attention Detection

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Artificial Intelligence, Medicine, Neurology,
auditory attention detection   electroencephalography   graph structure learning   graph convolutional network   neuro-steered hearing aids  

Application of Attention-guided Graph Structure Learning Network for EEG-enabled Auditory Attention Detection Academic Background The “cocktail party effect” describes the human brain’s ability to selectively concentrate attention on one speaker while ignoring others in a multi-talker environment. However, for individuals with hearing impairments, ...