With the growth of data and intelligent technologies, the healthcare sector opened numerous
technology that enabled services for patients, clinicians, and researchers. One major hurdle …

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 …

For many users of natural language processing (NLP), it can be challenging to obtain
concise, accurate and precise answers to a question. Systems such as question answering …

In this chapter, we present a survey on various decision support methods that uses ontology
as its tool to provide the reasoning, medical knowledge list, attributes and relationship …

Abstract Knowledge graphs (KGs) have recently become increasingly popular due to the
broad range of essential applications in various downstream tasks including intelligent …

Extant systems engineering standards are so fragmented that the conceptualization of a
cohesive body of knowledge is not easy. The discrepancies between different standards …

Knowledge bases store information on certain topics. Applying a well-structured and
machine-readable format for a knowledge base is a prerequisite for any AI-based …

Abstract Knowledge graph (KG) embedding methods predict missing links by computing the
similarities between entities. The existing embedding methods are designed with either …

Causal graphs play an essential role in the determination of causalities and have been
applied in many domains including biology and medicine. Traditional causal graph …

As the next step in the development of intelligent computing systems is the addition of
human expertise and knowledge, it is a priority to build strong computable and well …