Identifying population-based eGFR distributions may help to identify patients at risk for developing chronic kidney disease earlier, according to study data published in Kidney International. More ...
“Insurance is fundamentally a multi-party data ecosystem, but the way data moves has not kept pace with modern demands,” ...
Abstract: The increasing reliance on Large Language Models (LLMs) for health information seeking can pose severe risks due to the potential for misinformation and the complexity of these topics. This ...
Context graphs is the new buzzword for agentic Systems of Knowledge, uncovering the key role of the tribal knowledge hidden in decision threads that inform enterprise activity.
Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...
Text mining and knowledge graphs connect cell-culture parameters to glycosylation for faster bioprocess optimization.
Simplify the development of your next GenAI application with GraphRAG-SDK, a specialized toolkit for building Graph Retrieval-Augmented Generation (GraphRAG) systems. It integrates knowledge graphs, ...
Extensive knowledge graphs (KGs) have been constructed to facilitate knowledge-driven tasks across various scenarios. However, existing work usually develops separate reasoning models for different ...
Abstract: Aiming at the issue that most of the existing knowledge graph-based methods for personalized learning resource recommendations do not take full advantage of collaborative signals from ...
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