Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities

Abstract

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 graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge inference. However, in conjunction with a lack of a representative KG construction taxonomy, several existing approaches in this designated domain are inadequate and inferior. This paper is the first to provide a comprehensive taxonomy and a bird’s eye view of healthcare KG construction. Additionally, a thorough examination of the current state-of-the-art techniques drawn from academic works relevant to various healthcare contexts is carried out. These techniques are critically evaluated in terms of methods used for knowledge extraction, types of the knowledge base and sources, and the incorporated evaluation protocols. Finally, several research findings and existing issues in the literature are reported and discussed, opening horizons for future research in this vibrant area.

A systematic literature review of knowledge graph construction and application in education

“…Lack of Standardization : The absence of standardized formats or ontologies for educational KGs is another notable issue. Unlike more established KGs in domains like healthcare or finance [ 5 , 6 , 131 ], educational KGs lack a universally accepted structure. This makes sharing, integrating, or comparing KGs across different educational platforms or institutions challenging.…”

“…Moreover, domain-specific KGs have practical implications across various sectors. In industries like healthcare, a domain-specific KG could map medical conditions, treatments, and patient data, offering comprehensive insights for medical professionals [ 5 ]. In finance, a KG might interconnect economic indicators, market trends, and financial instruments, aiding analysts in making informed predictions [ [25] , [26] , [27] , [28] ].…”

“…These structured representations of knowledge have emerged as indispensable tools in education, catalysing advances driven by their increasingly recognized vital role in augmenting personalised learning, curriculum design, concept mapping, and educational content recommendation systems [ [1] , [2] , [3] , [4] ]. KGs are not a new concept; they have been utilized extensively in domains like healthcare [ 5 ], finance [ 6 ], transportation [ 7 ], business [ 8 ], and other domains [ [9] , [10] , [11] , [12] , [13] , [14] ]. However, their robust integration into the educational realm is a testament to their transformative potential.…”

A Data-Driven Paradigm for a Resilient and Sustainable Integrated Health Information Systems for Health Care Applications

“…Extant literature has heralded it as a multimodal paradigm that incorporates knowledge production and scientific discovery. 12 , 66 , 67 It is also considered to have evolved as a function to curb many ill-defined qualms associated with data, regardless of the discipline. Priestley and McGrath 66 posited these applications to be the catalysts emerging from the fusion of statistics and computer science at their peripheries, fashioning an academic “heterosis” that retort to the emergence of a novel problem set, for which the different silo discipline was ill-equipped to tackle.…”

“… 1 , 3 Several issues, such as data quality, security, and governance, are some of the prominent challenges constantly foreshowed in the healthcare context. 12 , 13 Thus, studies that explore the existing body of research on HIS for healthcare through data lenses are crucial. Therefore, the objective of this paper is to explore the existing body of research on HIS for healthcare through the data lens to present a data-driven paradigm for healthcare augmentation that is paramount to the attainment of sustainable and resilient HIS for healthcare.…”