Study on Different Brain Activation Rearrangement during Cognitive Workload from ERD/ERS and Coherence Analysis

Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Biophysics,
Event-Related Desynchronization   Event-Related Synchronization   Power Spectral Density   Coherence Analysis   Mental Arithmetic Task   EEG  

Study on Different Brain Activation Reorganization during Cognitive Load: ERD/ERS and Coherence Analysis Academic Background When humans engage in imagination, movement, or cognitive tasks, their brain functional activity patterns and activated regions differ. These pattern changes are also reflected in changes in brain electrical activity, which c...

Physiological Data for Affective Computing: The Affect-HRI Dataset

Information Science, Computer Science, Artificial Intelligence, Medicine, Environmental and Public Health, Neurology, Clinical Psychology,
affective computing   human-robot interaction   physiological data   service robots   emotion recognition   socio-technical   interdisciplinary research  

Application of Physiological Data in Human-Robot Interaction with Anthropomorphic Service Robots: Affect-HRI Dataset Background and Significance In interactions between humans and humans, as well as humans and robots, the interacting entity can influence human emotional states. Unlike humans, robots inherently cannot exhibit empathy and thus cannot...

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

Chemistry, Medicinal Chemistry, Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Pharmacy, Life Sciences, Immunology, Microbiology,
drug repurposing   network medicine   graph-based semi-supervised learning   COVID-19  

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...

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

Information Science, Computer Science, Artificial Intelligence, Medicine, Respiratory System, Medical Laboratory Science,
asthma prediction   asthma   affinity graph   feature selection   machine learning  

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

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-...

Graph Neural Network for Representation Learning of Lung Cancer

Graph Neural Network for Representation Learning of Lung Cancer

Information Science, Computer Science, Artificial Intelligence, Medicine, Respiratory System, Medical Imaging, Oncology,
multiple instance learning   graph   whole slide images   graph neural networks   lung cancer   variational autoencoder  

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,...