We developed a nanoparticle named OAF, which simultaneously targeted to both the brain and liver via the transferrin receptor 1 (TfR1) receptor, promoting lipoprotein receptor‐related protein 1 (LRP1) expression to enhance amyloid‐beta (Aβ) clearance. In AD mice model, OAF significantly reduced Aβ deposition and cognitive impairment, while a mitigating
Wenshuai Gong +8 more
wiley +1 more source
Automated Detection of Epileptic Seizures in EEG Signals via Micro-Capsule Networks. [PDF]
Wang B, Zhou J, Zhang H, Zhou J, Wang C.
europepmc +1 more source
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 more
wiley +1 more source
Construction of a Preoperative Prediction Model for TACE Resistance in Primary Hepatocellular Carcinoma Based on Machine Learning Algorithms. [PDF]
Jiao H, Zhang Z.
europepmc +1 more source
Image aesthetic quality assessment: A method based on deep convolutional capsule network. [PDF]
Hu Y, Dong W, Zhang Y, Lu L.
europepmc +1 more source
Artificial Intelligence in Gastrointestinal Motility Diagnostics: A Systematic Review. [PDF]
Muggleston D +3 more
europepmc +1 more source
Empowering genetic discoveries and cardiovascular risk assessment by predicting electrocardiograms from genotype. [PDF]
Lin S, Yang Y, Zhao H.
europepmc +1 more source
CEAF: Capsule network enhanced feature fusion architecture for Chinese Named Entity Recognition. [PDF]
Ma S, Liu G, Xu Y.
europepmc +1 more source
Reconsidering periosteal denervation: Anatomical redundancy and the limits of single-target interventions. [PDF]
Sonawane K.
europepmc +1 more source
Related searches:
Link prediction approach combined graph neural network with capsule network
Expert Systems With Applications, 2023Graph Neural Networks (GNNs, in short) are a powerful computational tool to jointly learn graph structure and node/edge features. They achieved an unprecedented accuracy in the link prediction problem, namely the task of predicting if two nodes are likely to be tied by an edge in the near future.
Giacomo Fiumara +2 more
exaly +2 more sources

