Recent advancements in deep learning architecture have increased its utility in real-life
applications. Deep learning models require a large amount of data to train the model. In …

Abstract Knowledge Graphs (KGs) have made a qualitative leap and effected a real
revolution in knowledge representation. This is leveraged by the underlying structure of the …

The incorporation of data analytics in the healthcare industry has made significant progress,
driven by the demand for efficient and effective big data analytics solutions. Knowledge …

Knowledge graphs are widely used in industry and studied within the academic community.
However, the models applied in the development of knowledge graphs vary. Analysing and …

Medical knowledge graphs (MKGs) are the basis for intelligent health care, and they have
been in use in a variety of intelligent medical applications. Thus, understanding the research …

The rapid development of information and communication technologies has enabled a value
co-creation paradigm for develo** industrial products and services, where massive …

Abstract Knowledge graph (KG) embedding models map nodes and edges to fixed-length
vectors and obtain the similarity of nodes as the output of a scoring function to predict …

The risk of discovering an intracranial aneurysm during the initial screening and follow-up
screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these …

Knowledge graph technology has important guiding significance for efficient and orderly
fault diagnosis of robot transmission system. Taking the historical robot maintenance logs of …

Electronic health records (EHRs) are an increasingly important source of information for
healthcare professionals and researchers. However, EHRs are often fragmented …