Results 61 to 70 of about 8,119,426 (288)
Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion [PDF]
Learning embeddings of entities and relations existing in knowledge bases allows the discovery of hidden patterns in them. In this work, we examine the contribution of geometrical space to the task of knowledge base completion. We focus on the family of translational models, whose performance has been lagging.
Prodromos Kolyvakis +2 more
openaire +2 more sources
Cancer‐associated mutations in endometriosis reframe a benign disease through molecular oncology
This review aims to comprehensively analyse cancer‐associated somatic mutations (CAMs) present in endometriotic lesions, emphasizing their biological roles, spatial distribution and implications for translational applications in medicine. By contextualizing a benign state within a genomic framework, this analysis seeks to establish its value as a ...
Clarissa Mujacic +15 more
wiley +1 more source
Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche +10 more
wiley +1 more source
Knowledge Graph Completion Integrating Relational Context Semantics [PDF]
Existing Knowledge Graph Completion (KGC) methods fail to effectively distinguish semantic differences among paths at different levels and cannot dynamically adjust relation representations by fully leveraging neighborhood context information ...
ZHAI Sheping, MA Mengyao, ZHANG Wenjing, YANG Rui
doaj +1 more source
Improving Hyper-Relational Knowledge Graph Completion
Different from traditional knowledge graphs (KGs) where facts are represented as entity-relation-entity triplets, hyper-relational KGs (HKGs) allow triplets to be associated with additional relation-entity pairs (a.k.a qualifiers) to convey more complex information.
Donghan Yu, Yiming Yang 0002
openaire +2 more sources
Partial inhibition of focal adhesion kinase (FAK) can paradoxically promote tumor growth, rather than simply producing a weaker antitumor effect than that observed with strong FAK suppression. In breast cancer and melanoma models, targeting p110δ PI3K, particularly in macrophages, counteracted these tumor‐promoting effects, highlighting the importance ...
Lydia Xenou +4 more
wiley +1 more source
Contextual language models for knowledge graph completion
Knowledge Graphs (KGs) have become the backbone of various machine learning based applications over the past decade. However, the KGs are often incomplete and inconsistent. Several representation learning based approaches have been introduced to complete the missing information in KGs. Besides, Neural Language Models (NLMs) have gained huge momentum in
Biswas, Russa +3 more
openaire +4 more sources
Gut microbiota alterations in patients with non‐small‐cell lung cancer undergoing chemoradiotherapy
We investigated the impact of concurrent chemoradiotherapy (CRT) on the gut microbiota in patients with locally advanced non‐small‐cell lung cancer. Overall gut microbiota composition remained largely stable throughout CRT while antibiotic exposure may influence microbial diversity.
Hanne Marte Nymoen +19 more
wiley +1 more source
Incomplete microwave ablation (iMWA) of liver cancer triggers a biphasic progression in residual tumors. At Day 3, the microenvironment is characterized by acute inflammatory responses and extracellular matrix (ECM) remodeling. By Day 14, a profound shift occurs toward oncogenic signal transduction and immunosuppression, marked by macrophage ...
Yu Liu +9 more
wiley +1 more source
Translation-Based Embeddings with Octonion for Knowledge Graph Completion
Knowledge representation learning achieves the automatic completion of knowledge graphs (KGs) by embedding entities into continuous low-dimensional vector space.
Mei Yu +7 more
doaj +1 more source

