Results 101 to 110 of about 1,057,004 (267)
Context-embedded hypergraph attention network and self-attention for session recommendation
Modeling user intention with limited evidence in short-term historical sequences is a major challenge in session recommendation. In this domain, research exploration extends from traditional methods to deep learning.
Zhigao Zhang +3 more
doaj +1 more source
Harnessing the Power of Attention for Patch-Based Biomedical Image Classification
The analysis of biomedical images, particularly brain MRI scans, is critical in healthcare and medical research. However, conventional approaches such as convolutional neural networks (CNNs) often struggle to capture complex spatial and contextual ...
Gousia Habib +5 more
doaj +1 more source
Self-Attention as a Predictor of EEG Anomalies
One of the main concerns when dealing with electroencephalographic signals (EEG) is assuring that clean data with a high signal-to-noise ratio is recorded. The relevant denoising methods tend to have a narrow scope of application as what is noise for one application might be useful signal for some other application and there no general-purpose approach
Natalia Koliou +4 more
openaire +2 more sources
Epigenetic reprogramming of lineage switching in cancer
Cancer cells rarely commit to a single identity. Epigenetic mechanisms and tumor microenvironment cues push epithelial cells toward flexible, hybrid states that can shift into mesenchymal, neuroendocrine, or stem‐like fates, driving metastasis, drug resistance, and tumor heterogeneity. Targeting the epigenetic regulators behind these transitions, using
Ezgi Boyvatlı +4 more
wiley +1 more source
Combining osimertinib with the STING agonist ADU‐S100 activates innate and adaptive immunity to overcome the non‐inflamed microenvironment of Egfr‐mutant lung cancer. This combination increases NK and CD8+ T‐cell infiltration, associated with activation of the STING‐IRF3 pathway and local immunogenic cell death.
Jun Nishimura +19 more
wiley +1 more source
TlcMHCpan: A Novel Deep Learning Model for Enhanced Pan-Specific Prediction of Peptide-HLA Binding
The interaction between Human Leukocyte Antigens (HLA) and peptides is key in cellular immunology and crucial for the development of the immune system and peptide-based drug design.
Xin Peng +3 more
doaj +1 more source
BCL9 and BCL9L drive bladder cancer progression by enhancing β‐catenin signaling, promoting proliferation, migration, invasion, and organoid growth. Genetic depletion of BCL9(L) suppresses malignant phenotypes, while pharmacological disruption of the β‐catenin/BCL9(L) complex with ZW4864 inhibits canonical Wnt signaling and tumor‐associated cellular ...
Roland Kotolloshi +11 more
wiley +1 more source
Commentary: Attentional control and the self: The Self Attention Network (SAN)
Adolfo M. García +7 more
doaj +1 more source
In this paper, we propose TransConvNet, a hybrid model combining Convolutional Neural Networks (CNNs), self-attention mechanisms, and transfer learning for wireless signal recognition under challenging conditions.
Wu Wei +3 more
doaj +1 more source
Derivation and characterization of retinal pigment epithelium from urine‐derived iPSCs
Age‐related macular degeneration causes vision loss via RPE dysfunction and loss. Traditional iPSC therapies rely on invasive biopsies, limiting scalability. Here, we utilize urine‐derived stem cells as an accessible source to generate u‐iPSCs, successfully differentiated into pigmented RPE. This “Urine‐to‐Retina” platform provides a promising path for
Daniella Beiner +7 more
wiley +1 more source

