BACKGROUND: Spatial transcriptomics technologies fully utilize spatial location information, tissue morphological features, and transcriptional profiles. Integrating these data can greatly advance our understanding about cell biology in the morpholog...
Neural networks : the official journal of the International Neural Network Society
Sep 9, 2023
Deep neural networks have become increasingly significant in our daily lives due to their remarkable performance. The issue of adversarial examples, which are responsible for the vulnerability problem of deep neural networks, has attracted the attent...
Neural networks : the official journal of the International Neural Network Society
Sep 9, 2023
In this paper, we investigate the problem of causal image classification with multi-label learning. As multi-label learning involves a diversity of supervision signals, it is considered a challenging issue to solve. Previous approaches have attempted...
BACKGROUND: Pre-procedural computed tomography (CT) imaging assessment of the aortic valvular complex (AVC) is essential for the success of transcatheter aortic valve replacement (TAVR). However, pre-TAVR assessment is a time-intensive process, and t...
BMC medical informatics and decision making
Sep 9, 2023
BACKGROUND: Food frequency questionnaires (FFQs) are one of the most useful tools for studying and understanding diet-disease relationships. However, because FFQs are self-reported data, they are susceptible to response bias, social desirability bias...
Journal of chemical information and modeling
Sep 8, 2023
Presently, the field of analyzing differentially expressed genes (DEGs) of RNA-seq data is still in its infancy, with new approaches constantly being proposed. Taking advantage of deep neural networks to explore gene expression information on RNA-seq...
BACKGROUND: Real-time tumor tracking is one motion management method to address motion-induced uncertainty. To date, fiducial markers are often required to reliably track lung tumors with X-ray imaging, which carries risks of complications and leads ...
Electroencephalography is a method of detecting and analyzing electrical activity in the brain. This electrical activity can be recorded and processed to aid in the clinical diagnosis of mental disorders. In this study, a novel system for classifying...
Aging clinical and experimental research
Sep 8, 2023
The increasing access to health data worldwide is driving a resurgence in machine learning research, including data-hungry deep learning algorithms. More computationally efficient algorithms now offer unique opportunities to enhance diagnosis, risk s...
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