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Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities
by
AL-Qurishi, Muhammad
, Alfayez, Reem
, Saadeh, Heba
, Abu-Salih, Bilal
, Alweshah, Mohammed
, AL-Smadi, Mohammad
in
Big Data
/ Classification
/ Data analysis
/ Evaluation research
/ Extraction
/ Graphs
/ Health care
/ Health care industry
/ Health services
/ Inference
/ Knowledge
/ Knowledge base
/ Knowledge bases (artificial intelligence)
/ Knowledge representation
/ State-of-the-art reviews
/ Systematic review
/ Taxonomy
2023
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Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities
by
AL-Qurishi, Muhammad
, Alfayez, Reem
, Saadeh, Heba
, Abu-Salih, Bilal
, Alweshah, Mohammed
, AL-Smadi, Mohammad
in
Big Data
/ Classification
/ Data analysis
/ Evaluation research
/ Extraction
/ Graphs
/ Health care
/ Health care industry
/ Health services
/ Inference
/ Knowledge
/ Knowledge base
/ Knowledge bases (artificial intelligence)
/ Knowledge representation
/ State-of-the-art reviews
/ Systematic review
/ Taxonomy
2023
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Do you wish to request the book?
Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities
by
AL-Qurishi, Muhammad
, Alfayez, Reem
, Saadeh, Heba
, Abu-Salih, Bilal
, Alweshah, Mohammed
, AL-Smadi, Mohammad
in
Big Data
/ Classification
/ Data analysis
/ Evaluation research
/ Extraction
/ Graphs
/ Health care
/ Health care industry
/ Health services
/ Inference
/ Knowledge
/ Knowledge base
/ Knowledge bases (artificial intelligence)
/ Knowledge representation
/ State-of-the-art reviews
/ Systematic review
/ Taxonomy
2023
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Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities
Journal Article
Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities
2023
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Overview
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.
Publisher
Springer Nature B.V
Subject
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