IEEE journal of biomedical and health informatics
Dec 5, 2024
OBJECT: Transformer-based neural networks have been applied to the electroencephalography (EEG) decoding for motor imagery (MI). However, most networks focus on applying the self-attention mechanism to extract global temporal information, while the c...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Identifying circular RNA (circRNA)-drug sensitivity association (CDsA) is crucial for advancing drug development. As conducting traditional wet experiments for determining CDsA is costly and inefficient, calculation methods have already proven to be ...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Developing deep learning models for accurate segmentation of biomedical CT images is challenging due to their complex structures, anatomy variations, noise, and unavailability of sufficient labeled data to train the models. There are many models in t...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Accurate fovea localization is essential for analyzing retinal diseases to prevent irreversible vision loss. While current deep learning-based methods outperform traditional ones, they still face challenges such as the lack of local anatomical landma...
IEEE journal of biomedical and health informatics
Dec 5, 2024
By modeling the temporal dependencies of sleep sequence, advanced automatic sleep staging algorithms have achieved satisfactory performance, approaching the level of medical technicians and laying the foundation for clinical assistance. However, exis...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Objective - Medical image segmentation is essential for several clinical tasks, including diagnosis, surgical and treatment planning, and image-guided interventions. Deep Learning (DL) methods have become the state-of-the-art for several image segmen...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Extensive research indicates that microRNAs (miRNAs) play a crucial role in the analysis of complex human diseases. Recently, numerous methods utilizing graph neural networks have been developed to investigate the complex relationships between miRNAs...
IEEE journal of biomedical and health informatics
Dec 5, 2024
This paper presents a novel motor imagery classification algorithm that uses an overlapping multiscale multiband convolutional Riemannian network with band-wise Riemannian triplet loss to improve classification performance. Despite the superior perfo...
IEEE journal of biomedical and health informatics
Dec 5, 2024
The global prevalence of mental health disorders is increasing, leading to a significant economic burden estimated in trillions of dollars. In automated mental health diagnosis, the scarcity and imbalance of clinical data pose considerable challenges...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for estimating brain age. However, the over-squashing impedes interactions between long-range nodes, hindering the ability of message-passing mechanism-bas...
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