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...

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

Medicine, Psychiatry, Neurology, Clinical Psychology, Medical Imaging,
cross-frequency coupling   resting EEG signals   major depressive disorder   depression severity classification   machine learning  

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...

Distinguishing Parkinsonian Rest Tremor from Voluntary Hand Movements through Subthalamic and Cortical Activity

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Life Sciences, Biophysics,
Parkinson’s disease   rest tremor   voluntary hand movements   brain activity   subthalamic nucleus   machine learning  

Parkinson’s disease (PD) is a common neurodegenerative disorder characterized mainly by resting tremor, bradykinesia, and rigidity. Deep Brain Stimulation (DBS) has been widely used to treat the motor symptoms of PD (Krauss et al., 2021). However, DBS treatment also has significant side effects, most of which are caused by the extension of stimulat...

The Role of EEG Microstates in Predicting Oxcarbazepine Treatment Outcomes in Patients with Newly-Diagnosed Focal Epilepsy

The Role of EEG Microstates in Predicting Oxcarbazepine Treatment Outcomes in Patients with Newly-Diagnosed Focal Epilepsy

Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging,
EEG microstates   antiseizure medications   oxcarbazepine   machine learning   epilepsy  

The Role of EEG Microstates in Predicting the Therapeutic Outcomes of Oxcarbazepine in Newly Diagnosed Focal Epilepsy Patients Introduction Background Focal epilepsy is the most common type of epilepsy, accounting for about 60% of all epilepsy cases. The selection of antiepileptic drugs (AEDs) varies depending on the type of epilepsy. In the treatm...

Deep Learning-Based Assessment Model for Real-Time Identification of Visual Learners Using Raw EEG

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Bioengineering,
deep learning   real-time identification   visual learners   EEG   machine learning   electroencephalogram   classification  

In the current educational environment, understanding students’ learning styles is crucial for improving their learning efficiency. Specifically, the identification of visual learning styles can help teachers and students adopt more effective strategies in the teaching and learning process. Currently, automatic identification of visual learning sty...