Clinical Trial and Disease Search with Ad Hoc Interactive Ontology Alignments

  • Daniel Sonntag
  • Jochen Setz
  • Maha Ahmed-Baker
  • Sonja Zillner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7295)


We will explain how an LODD application based on diseases, drugs, and clinical trials can be used to improve the (ontology-based) clinical reporting process while, at the same time, it improves the patient follow-up treatment process. Specific requirements of the radiology domain let us aggregate RDF results from several LODD sources such as DrugBank, Diseasome, DailyMed, and LinkedCT. The idea is to use state-of-the-art string matching algorithms which allow for a ranked list of candidates and confidences of the approximation of the distance between two diseases at query time. Context information must be provided by the clinician who decides on the “related”-mappings of patient context and links he wants to follow in order to retrieve disease and medication information.


Mantle Cell Lymphoma String Match Ontology Match Ontology Alignment String Match Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Daniel Sonntag
    • 1
  • Jochen Setz
    • 1
  • Maha Ahmed-Baker
    • 1
  • Sonja Zillner
    • 2
  1. 1.German Research Center for AI (DFKI)SaarbrueckenGermany
  2. 2.Siemens AG, Corporate TechnologyMunichGermany

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