Drug Side Effects Data Representation and Full Spectrum Inferencing Using Knowledge Graphs in Intelligent Telehealth

Saravanan Jayaraman, Lixin Tao*, Keke Gai, Ning Jiang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

Drug side effects data contains important constraints about side-effects and conflict avoidance of component and compound drug. These are critically important in checking out prescriptions to avoid complications. Current drug data side effect representations in XML does not have a proper knowledge representation mechanism to clearly specify all kinds of dependencies among the drug components and drugs. Therefore Doctors and caregivers often rely on human interpretation to check prescriptions which can be error-prone. The recently introduced Web Ontology Language (OWL) based approach for medical drug side effects data representation still suffers from several shortcomings inherent to the OWL restrictions like using " is-a " relationship and usage of object property based workarounds losing the clarity and dynamic relationship building expected by domain experts to represent knowledge. The proposed model Drug-Side Effects Representation And Inferencing (D-SERI) built using Knowledge Graph (KG) and enhanced PaceJena shows that the proposed model allowsthe doctors and caregivers to derive dynamic information about side effects avoiding costly errors caused by human interpretation.

Original languageEnglish
Title of host publicationProceedings - 3rd IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2016 and 2nd IEEE International Conference of Scalable and Smart Cloud, SSC 2016
EditorsLixin Tao, Meikang Qiu, Jianwei Niu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages289-294
Number of pages6
ISBN (Electronic)9781509009459
DOIs
Publication statusPublished - 16 Aug 2016
Externally publishedYes
Event3rd IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2016 and 2nd IEEE International Conference of Scalable and Smart Cloud, SSC 2016 - Beijing, China
Duration: 25 Jun 201627 Jun 2016

Publication series

NameProceedings - 3rd IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2016 and 2nd IEEE International Conference of Scalable and Smart Cloud, SSC 2016

Conference

Conference3rd IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2016 and 2nd IEEE International Conference of Scalable and Smart Cloud, SSC 2016
Country/TerritoryChina
CityBeijing
Period25/06/1627/06/16

Keywords

  • Data representation
  • Intelligent Telehealth
  • full spectrum inference
  • knowledge graph

Fingerprint

Dive into the research topics of 'Drug Side Effects Data Representation and Full Spectrum Inferencing Using Knowledge Graphs in Intelligent Telehealth'. Together they form a unique fingerprint.

Cite this