PURPOSE: To evaluate the clinimetric reliability of automated vestibular schwannoma (VS) segmentations by a comparison with human inter-observer variability on T1-weighted contrast-enhanced MRI scans.
IEEE journal of biomedical and health informatics
Apr 4, 2025
The sparse surface electromyography-based gesture recognition suffers from the problems of feature information not richness and poor generalization to small sample data. Therefore, a multi-feature fusion network (MFF-Net) model is proposed in this pa...
IEEE journal of biomedical and health informatics
Apr 4, 2025
Brain-computer interfaces (BCIs) based on steady-state visual evoked potential (SSVEP) signals offer high information transfer rates and non-invasive brain-to-device connectivity, making them highly practical. In recent years, deep learning technique...
IEEE journal of biomedical and health informatics
Apr 4, 2025
Inertial measurement units (IMUs) have become attractive for monitoring joint kinematics due to their portability and versatility. However, their limited accuracy, inability to analyze data in real-time, and complex data fusion algorithms requiring p...
IEEE journal of biomedical and health informatics
Apr 4, 2025
Deformable image registration, as a fundamental prerequisite for many medical image analysis tasks, has received considerable attention. However, existing methods suffer from two key issues: 1) single-stream methods that stack moving and fixed images...
IEEE journal of biomedical and health informatics
Apr 4, 2025
Electroencephalography (EEG) plays a crucial role in the diagnosis of various neurological disorders. However, small hospitals and clinics often lack advanced EEG signal analysis systems and are prone to misinterpretation in manual EEG reading. This ...
IEEE journal of biomedical and health informatics
Apr 4, 2025
Thanks to advancements in artificial intelligence and brain-computer interface (BCI) research, there has been increasing attention towards emotion recognition techniques based on electroencephalogram (EEG) recently. The complexity of EEG data poses a...
IEEE transactions on neural networks and learning systems
Apr 4, 2025
Benefiting from the high-temporal resolution of electroencephalogram (EEG), EEG-based emotion recognition has become one of the hotspots of affective computing. For EEG-based emotion recognition systems, it is crucial to utilize state-of-the-art lear...
BACKGROUND: This study aimed to evaluate the relationship between CBC-derived inflammatory markers (NLR, PLR, NPAR, SII, SIRI, and AISI) and all-cause mortality (ACM) risk in arthritis (AR) patients with hypertensive (HTN) using data from the NHANES.