Deep learning has seen significant growth recently and is now applied to a wide range of
conventional use cases, including graphs. Graph data provides relational information …

In the dynamic landscape of modern education, the search for improved pedagogical
methods, enriched learning experiences, and empowered educators remains a perpetual …

In the current digitalization era, capturing and effectively representing knowledge is crucial
in most real-world scenarios. In this context, knowledge graphs represent a potent tool for …

Recently, recommender systems have been combined with healthcare systems to
recommend needed healthcare items for both patients and medical staff. By monitoring the …

Introduction Constructing an accurate and comprehensive knowledge graph of specific
diseases is critical for practical clinical disease diagnosis and treatment, reasoning and …

Abstract Knowledge graphs (KGs) are constructed by extracting knowledge triples from text
and fusing knowledge, enhancing information retrieval efficiency. Current methods for …

Diagnostic accuracy plays a pivotal role in healthcare, directly affecting treatment efficacy
and patient outcomes. Errors in diagnosis can result in inappropriate or delayed treatments …

Single-cell RNA sequencing (scRNA-seq) has transformed biological research, enabling
detailed analysis of disease pathways, cellular differentiation, and immune responses at a …

Background The growth of biomedical literature presents challenges in extracting and
structuring knowledge. Knowledge Graphs (KGs) offer a solution by representing …

Objective Designing a new clinical trial entails many decisions, such as defining a cohort
and setting the study objectives to name a few, and therefore can benefit from …