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...

Research Background and Objectives With the continuous development of neuroscience, identifying indirectly observed processes related to functional networks has become an important research direction. Researchers attempt to estimate the activity of these functional networks through electrophysiological signals such as EEG and MEG. However, this pro...

Study on the Relationship between Macroscopic Intrinsic Dynamics and Microcircuit Functions in Epilepsy Research Background Epilepsy is a group of neurological disorders characterized by abnormal spontaneous brain activity, involving multi-scale changes in brain functional organization. However, it remains unclear to what extent epilepsy-related sp...

Research Report on Potential Biomarkers for Early Detection of ADHD: Phase-Based Functional Brain Connectivity and Graph Theory Analysis This is a research report titled “Potential Biomarkers for Early Detection of ADHD: Using Phase-Based Functional Brain Connectivity and Graph Theory Analysis”. This study was conducted by Farhad Abedinzadeh Torgha...

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-...

Representation Learning of Lung Cancer Based on Graph Neural Networks Background Introduction With the rapid development of digital pathology, image-based diagnostic systems are becoming increasingly important in precise pathological diagnosis. These systems rely on Multiple Instance Learning (MIL) technology for Whole Slide Images (WSIs). However,...

Graph Theory Analysis of Brain Network Topology Structure in Patients with Primary Angle-Closure Glaucoma Research Background Glaucoma is a global blinding eye disease characterized by optic nerve damage and elevated intraocular pressure (IOP) (Kang and Tanna 2021). Among various types of glaucoma, Primary Angle-Closure Glaucoma (PACG) is particula...

Changes in Functional Brain Networks in Coronary Heart Disease Patients: Independent Component Analysis and Graph Theory Analysis This article, published in the 229th volume of “Brain Structure and Function” in 2024, explores the changes in functional connectivity (FC) and brain network topology in patients with coronary heart disease (CHD). The st...

Research Report on Immunotherapy Efficacy Prediction for Non-Small Cell Lung Cancer: A Study of Multi-View Adaptive Weighted Graph Convolutional Networks Background Introduction Lung cancer is a highly prevalent and poorly prognostic malignant tumor with a persistently high mortality rate. Among all lung cancer patients, Non-Small Cell Lung Cancer ...

CIGNN: A Framework for Cuffless Continuous Blood Pressure Estimation Based on Causality and Graph Neural Networks Background Introduction According to data from the World Health Organization (WHO), approximately 1.13 billion people globally are affected by hypertension, and this number is expected to increase to 1.5 billion by 2025. Hypertension is...