IEEE journal of biomedical and health informatics
Apr 4, 2025
The prevalence of Alzheimer's disease (AD) is rising annually, imposing a severe burden on patients and society. Therefore, assisted AD assessment is crucial. The decline in language function and the cognitive impairment it reflects are key external ...
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
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 transactions on neural networks and learning systems
Apr 4, 2025
Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and irreversible dementia; thus, predicting its progression over time is vital for clinical diagnosis and treatment. For this, numerous studies have imple...
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.
INTRODUCTION: This study investigates the potential of a deep learning-based Life Log Sharing Model (LLSM) to enhance adolescent physical fitness and exercise behaviors through personalized public health interventions.
Esophageal cancer is one of the most common cancers worldwide, especially esophageal squamous cell carcinoma, which is often diagnosed at a late stage and has a poor prognosis. This study aimed to develop an algorithm to detect tumors in esophageal e...
The aim of the study was to determine how depression and cognitive dysfunction in patients with chronic hepatitis C virus (HCV) infection are affected by treatment with direct-acting antivirals (DAA). Fifty-two chronic hepatitis C patients underwent ...
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