IEEE transactions on neural networks and learning systems
May 2, 2025
Low-dose computed tomography (LDCT) image reconstruction techniques can reduce patient radiation exposure while maintaining acceptable imaging quality. Deep learning (DL) is widely used in this problem, but the performance of testing data (also known...
Astrocytes regulate synaptic activity across large brain territories via their complex, interconnected morphology. Emerging evidence supports the involvement of astrocytes in shaping relapse to opioid use through morphological rearrangements in the n...
Neural networks : the official journal of the International Neural Network Society
Apr 29, 2025
Neural networks, while powerful, often face significant challenges in terms of interpretability, particularly in clustering tasks. Traditional methods typically rely on post-hoc explanations or supervised learning, which limit their ability to provid...
Passive acoustic monitoring can offer insights into the state of coral reef ecosystems at low-costs and over extended temporal periods. Comparison of whole soundscape properties can rapidly deliver broad insights from acoustic data, in contrast to de...
International journal of medical informatics
Apr 26, 2025
BACKGROUND: Our objective was to identify distinct clinical subtypes among critically ill patients with cirrhosis and analyze the clinical features and prognosis of each subtype.
Journal of applied clinical medical physics
Apr 23, 2025
BACKGROUND: Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning-based automatic segmentation methods rely on manually annotated data for network training.
Unsupervised deformable multimodal medical image registration often confronts complex scenarios, which include intermodality domain gaps, multi-organ anatomical heterogeneity, and physiological motion variability. These factors introduce substantial ...
Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning increasingly plays a role, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in...
This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differential anti-vascular endothelial growth factor (VEGF) treatment outcomes using an unsupervised machine learning (ML) approach based on radiomic feature...
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