Analysis of Reading-Task-Based Brain Connectivity in Dyslexic Children Using EEG Signals

Brain Connectivity Analysis Based on Reading Tasks in Children with Dyslexia (Using EEG Signals) Dyslexia is a neurodevelopmental disorder that affects the normal reading ability, even though children with normal intelligence may still be affected. This paper investigates the differences in brain connectivity between children with dyslexia and norm...

Development of Complemented Comprehensive Networks for Rapid Screening of Repurposable Drugs Applicable to New Emerging Disease Outbreaks

Research on Network Construction and Application of Novel Drug Repositioning Strategies Background During the COVID-19 pandemic, researchers and pharmaceutical companies have been dedicated to developing treatments and vaccines. Drug repositioning, due to its shortcut, is considered a rapid and effective response strategy. Drug repositioning attemp...

Potential Biomarker for Early Detection of ADHD Using Phase-Based Brain Connectivity and Graph Theory

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 Neural Mechanism of Knowledge Assembly in the Human Brain Inspires Artificial Intelligence Algorithm

The Neural Mechanism of Knowledge Assembly in the Human Brain Inspires Artificial Intelligence Algorithm

Brain Science Research Inspires AI Algorithms: Neural Mechanisms of Knowledge Assembly Background Introduction When new information enters the brain, human pre-existing knowledge of the world can quickly change through a process called “knowledge assembly.” Recently, in a study conducted by Nelli et al., the neural correlates of knowledge assembly ...

Asthma Prediction via Affinity Graph Enhanced Classifier: A Machine Learning Approach Based on Routine Blood Biomarkers

Asthma Prediction Enhanced by Affinity Graph-Based Classifier: A Machine Learning Approach Using Routine Blood Biomarkers Background Asthma is a chronic respiratory disease that affects approximately 235 million people worldwide. According to the World Health Organization (WHO), the main characteristic of asthma is airway inflammation, leading to s...

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

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-...

Graph Neural Network for Representation Learning of Lung Cancer

Graph Neural Network for Representation Learning of Lung Cancer

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,...

Topological Organization of the Brain Network in Patients with Primary Angle-Closure Glaucoma through Graph Theory Analysis

Topological Organization of the Brain Network in Patients with Primary Angle-Closure Glaucoma through Graph Theory Analysis

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...

Functional Connectivity Alterations in Patients with Post-Stroke Epilepsy Based on Source-Level EEG and Graph Theory

Research Report on Changes in Functional Connectivity in Post-Stroke Epilepsy (PSE) Patients Based on Source-Level EEG and Graph Theory Research Background Epilepsy has various etiologies, including idiopathic, congenital, head trauma, central nervous system infections, brain tumors, neurodegenerative diseases, and cerebrovascular diseases. Among t...

Altered Functional Brain Networks in Coronary Heart Disease: Independent Component Analysis and Graph Theoretical Analysis

Altered Functional Brain Networks in Coronary Heart Disease: Independent Component Analysis and Graph Theoretical Analysis

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...