Weighted entity linking and integration algorithm for medical knowledge graph generation
Joint Authors
Shaban, Iman
Tantawi, Manal
Maghawiri, Nura
Imarah, Karim
Source
International Journal of Intelligent Computing and Information Sciences
Issue
Vol. 23, Issue 1 (31 Mar. 2023), pp.1-17, 17 p.
Publisher
Ain Shams University Faculty of Computer and Information Sciences
Publication Date
2023-03-31
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Semantic data integration is the process of interrelating information from multiple heterogeneous resources.
there is a need for representing data concepts and their relationships to eliminate heterogeneity among different data sources in healthcare management systems.
standardized medical ontologies provide predefined medical vocabulary serving as a stable interface for concepts related to medical data sources.
however, different ontologies have different concepts although these concepts have logical relations between them such as the human disease ontology and the symptoms ontology.
there aroused a need for a knowledge graph providing a reliable knowledge base for any intelligent healthcare expert advisor disease prediction system.
the knowledge graph provides a model for linking and integrating different concepts having logical relationships such as diseases and their symptoms.
medical online website and encyclopedia provides a reliable source for building such a knowledge graph.
the knowledge graph is enriched with social networks data where information extracted reflects a major source of data based on user experiences.
the paper proposes a framework for constructing a disease-symptom entity linked knowledge graph based on online medical encyclopedia and social networks user experiences.
entity linking such an integrated knowledge graph with standardized medical ontologies makes it a reliable knowledge base for a standard system that could be used by social networks user and the professional staff.
American Psychological Association (APA)
Maghawiri, Nura& Tantawi, Manal& Shaban, Iman& Imarah, Karim. 2023. Weighted entity linking and integration algorithm for medical knowledge graph generation. International Journal of Intelligent Computing and Information Sciences،Vol. 23, no. 1, pp.1-17.
https://search.emarefa.net/detail/BIM-1460747
Modern Language Association (MLA)
Maghawiri, Nura…[et al.]. Weighted entity linking and integration algorithm for medical knowledge graph generation. International Journal of Intelligent Computing and Information Sciences Vol. 23, no. 1 (Mar. 2023), pp.1-17.
https://search.emarefa.net/detail/BIM-1460747
American Medical Association (AMA)
Maghawiri, Nura& Tantawi, Manal& Shaban, Iman& Imarah, Karim. Weighted entity linking and integration algorithm for medical knowledge graph generation. International Journal of Intelligent Computing and Information Sciences. 2023. Vol. 23, no. 1, pp.1-17.
https://search.emarefa.net/detail/BIM-1460747
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 15-17
Record ID
BIM-1460747