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...
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...
Thalamocortical Connectivity Reduction in Rolandic Epilepsy Rolandic Epilepsy (RE), also known as self-limited epilepsy with centrotemporal spikes (SELECTS), is the most common localized developmental epileptic encephalopathy. This type of epilepsy is typically accompanied by transient mild to severe cognitive symptoms, sleep-related rolandic spike...
Changes in Functional Connectivity in Mild Cognitive Impairment: A Meta-Analysis of M/EEG Studies Background and Objectives Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by memory loss and cognitive impairment. AD is the leading cause of cognitive disorders in the elderly, accounting for approximately 60% to 80% of global c...
Background Depression, particularly Major Depressive Disorder (MDD), is a widespread and debilitating psychological disease often described as the “common cold” of mental health. Many people with MDD experience symptoms such as persistent sadness, hopelessness, cognitive impairment, and loss of motivation for daily activities, severely affecting pe...