Bloodstream infections caused by spp. are among the leading hospital-acquired infections, but their diagnosis remains slow and challenging with conventional culture-based methods, which often require days to deliver results. This study aimed to deve...
Bacterial-mediated drug delivery has emerged as a promising strategy for disease treatment, leveraging bacteria's innate ability to penetrate biological barriers and target diseased tissues. However, existing bacteria-nanoparticle hybrid systems ofte...
. Accurate dose accumulation relies on deformable image registration (DIR) to track dose across multiple images. However, DIR introduces uncertainties that can impact cumulative dose distributions. In this study, we present a probabilistic framework ...
Messenger RNA (mRNA) vaccines face core challenges including low-delivery efficiency and immunogenicity, limiting their wide-ranging applications in infectious disease prevention and cancer therapy. Lipid nanoparticles (LNPs), the most clinically val...
OBJECTIVE: Acute respiratory distress syndrome (ARDS) is estimated to be prevalent in 10% of ICU patients and results in high mortality rates of up to 45%. The recognition of ARDS can be complex and is often delayed or missed entirely. Recognition of...
Graph neural networks (GNNs) have emerged as a state-of-the-art data-driven tool for modeling connectivity data of graph-structured complex networks and integrating information of their nodes and edges in space and time. However, as of yet, the analy...
Studies in neuroscience inspired progress in the design of artificial neural networks (ANNs), and, vice versa, ANNs provide new insights into the functioning of brain circuits. So far, the focus has been on how ANNs can help to explain the tuning of ...
With the rapid advancement of cross-border e-commerce, accurately predicting user purchase behavior has emerged as a critical challenge for enhancing platform operational efficiency and user experience. This study proposes a hybrid deep learning fram...
Sign language recognition is crucial in bridging the communication gaps between hearing and deaf communities. In this study, we build on an existing sign language classification model based on the VGG19 architecture, enhancing its robustness through ...
Dementia is among the most distressing and burdensome health challenges in aging populations. Treatment efficacy is limited; however, early diagnosis can delay or prevent disease progression. Previous machine learning-based prediction models have lim...
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