Automated intelligent online healthcare ontology Integration

Maghawry, Noura; Emara, Karim; Shaaban, Eman; Ghoniemy, Samy

doi:10.1109/icci54321.2022.9756070

Cited by 3 publications

(1 citation statement)

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“…The second stage is extracting concepts from the DO, where the third stage is integrating the generated knowledge graph from stage one with the standard ontology concepts. (Maghawry, Emara, Shaaban, & Ghoniemy, 2022) Figure 3 Proposed system (Maghawry, Emara, Shaaban, & Ghoniemy, 2022) The Knowledge Collaboratory is a web service to query and publish Nanopublications for the NCATS Biomedical Data Translator project. It can Browse Nanopublications through the web UI, or query them using the Translator Reasoner API (TRAPI) specifications or Publish Nanopublications after login with ORCID, and uploading your authentication keys to the server.…”

Section: Technologies Used In Construction Of Knowledge Graph In Heal...mentioning

confidence: 99%

Exploiting Knowledge Graphs in Healthcare

Maxhelaku¹,

Xhumari²,

Xhina³

2022

Proceedings of the 16th Economics &Amp; Finance Conference, Prague

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The use of knowledge graphs in health care has increased the performance in which information is retrieved and patients' diagnoses are made. Because the healthcare domain is made up of complex concepts and many relationships between them, developing knowledge graphs presents numerous challenges. Another issue is the large number of medical standards, such as HL7, ICD-10, SNOMED CT, DICOM, LOINC, and so on. In this paper are analyzed the technologies used in the construction of knowledge graphs in healthcare. In addition, a model for generating knowledge graphs from the APHRO (Albanian Patient Healthcare Records) Ontology is proposed.

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Section: Technologies Used In Construction Of Knowledge Graph In Heal...mentioning

confidence: 99%