IEEE journal of biomedical and health informatics
Jan 7, 2025
Currently, spatiotemporal convolutional neural networks (CNNs) for electroencephalogram (EEG) signals have emerged as promising tools for seizure prediction (SP), which explore the spatiotemporal biomarkers in an epileptic brain. Generally, these CNN...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Domain adaptation has demonstrated success in classification of multi-center autism spectrum disorder (ASD). However, current domain adaptation methods primarily focus on classifying data in a single target domain with the assistance of one or multip...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, a dual-branch network for segmenting acute ischemi...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Diffusion tensor imaging (DTI) is a prevalent magnetic resonance imaging (MRI) technique, widely used in clinical and neuroscience research. However, the reliability of DTI is affected by the low signal-to-noise ratio inherent in diffusion-weighted (...
IEEE journal of biomedical and health informatics
Jan 7, 2025
The excessive consumption of marijuana can induce substantial psychological and social consequences. In this investigation, we propose an elucidative framework termed high-order graph attention neural networks (HOGANN) for the classification of Marij...
IEEE journal of biomedical and health informatics
Jan 7, 2025
Emerging researchindicates that the degenerative biomarkers associated with Alzheimer's disease (AD) exhibit a non-random distribution within the cerebral cortex, instead following the structural brain network. The alterations in brain networks occur...
Zhongguo zhen jiu = Chinese acupuncture & moxibustion
Jan 6, 2025
OBJECTIVE: To screen the population for acupuncture treatment of neck pain, using functional magnetic resonance imaging (fMRI) technology and based on machine learning algorithms.
BACKGROUND: Recognition of emotion changes is of great significance to a person's physical and mental health. At present, EEG-based emotion recognition methods are mainly focused on time or frequency domains, but rarely on spatial information. Theref...
Artificial intelligence (AI) tools can triage radiology scans to streamline the patient pathway and also relieve clinician workload. Validated AI tools can mitigate the delays in reporting scans by flagging time-sensitive and actionable findings. In ...
By gaining insights into how brain activity is encoded and decoded, we enhance our understanding of brain function. This study introduces a method for classifying EEG signals related to visual objects, employing a combination of an LSTM network and n...
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