CIGNN: A Causality-Informed and Graph Neural Network Based Framework for Cuffless Continuous Blood Pressure Estimation

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 Networks for Major Depressive Disorder Diagnosis with Synthetic Functional Brain Network Generation

Graph-based Conditional Generative Adversarial Networks for Major Depressive Disorder Diagnosis with Synthetic Functional Brain Network Generation

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...

Decreased Thalamocortical Connectivity in Resolved Rolandic Epilepsy

Decreased Thalamocortical Connectivity in Resolved Rolandic Epilepsy

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...

Functional Connectivity Changes in Mild Cognitive Impairment: A Meta-Analysis of M/EEG Studies

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...

Investigation of the Impact of Cross-Frequency Coupling on the Assessment of Depression Severity through the Analysis of Resting State EEG Signals

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...