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Accelerating the Exploitation of (bio)medical Knowledge Using Linked Data

  • Mohammad ShafahiEmail author
  • Hamideh Afsarmanesh
  • Hayo Bart
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 690)

Abstract

Early identification and treatment of a diseases, especially when chronic, can reduce severe complications for the patients, doctors, and the society as a whole. Therefore, becoming aware and having insight about the state of the art findings on diseases, if communicated properly to different stakeholders, will benefit all. The medical research field, however, is vast and dynamically evolves with new discoveries. Additionally, new results are being continuously generated. The new discoveries on diseases address their diagnosis, prognosis, and possible treatment pathways for each disease, which are typically published in medical articles. Research results, however, are not reflected in practice by practitioners, unless they are officially verified by governments and authoritative health institutes, and appear in medical guidelines. Developing the medical guidelines requires identifying every relevant medical article, traversing through and validating it, as well as gathering and inter-relating that data to the information from other relevant sources, such as the drug interaction databases.

Therefore, optimal exploitation of medical advances and research results by all its stakeholders, being researchers, practitioners, and patients, is essential. This, however, is hindered due to both the lack of integration of their typically disparate information, and the lack of facilities for coherent, up-to-date, and personalized access by their stakeholders. The few researches that address these issues do not sufficiently address the needed dynamism in data, lack intuitiveness in their use, and present a rather limited amount of information, which is usually obtained from a single source. This research aims to address these gaps through the development of BioMed Xplorer, presenting a model and a tool that enables researchers to rapidly query and explore biomedical knowledge from multiple sources, while preserving provenance data, and presenting all inter-linked information through an intuitive and personalized user interface. Results are further validated by some domain experts, through contrasting it against the state of the art, and with a task-based validation experimenting with the real case of updating medical guidelines.

Keywords

BioMed Xplorer Disease related information Semantic Web Knowledge base ontology Visualization Provenance data Medical knowledge External data source RDF Graph Knowledge exploration 

Notes

Acknowledgements

This work was carried out on the Dutch national e-infrastructure with the support of SURF Foundation. We also like to thank the School of Medicine at Democritus University of Trace for helping with some requirements identification and validation.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mohammad Shafahi
    • 1
    Email author
  • Hamideh Afsarmanesh
    • 1
  • Hayo Bart
    • 1
  1. 1.Faculty of Science, Informatics InstituteUniversity of AmsterdamAmsterdamThe Netherlands

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