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Rare Disease Diagnosis as an Information Retrieval Task

  • Radu Dragusin
  • Paula Petcu
  • Christina Lioma
  • Birger Larsen
  • Henrik Jørgensen
  • Ole Winther
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6931)

Abstract

Increasingly more clinicians use web Information Retrieval (IR) systems to assist them in diagnosing difficult medical cases, for instance rare diseases that they may not be familiar with. However, web IR systems are not necessarily optimised for this task. For instance, clinicians’ queries tend to be long lists of symptoms, often containing phrases, whereas web IR systems typically expect very short keyword-based queries. Motivated by such differences, this work uses a preliminary study of 30 clinical cases to reflect on rare disease retrieval as an IR task. Initial experiments using both Google web search and offline retrieval from a rare disease collection indicate that the retrieval of rare diseases is an open problem with room for improvement.

Keywords

rare diseases clinical information retrieval web diagnosis 

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References

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    Bouwman, M.G., Teunissen, Q.G.A., Wijburg, F.A., Linthorst, G.E.: Doctor Google ending the diagnostic odyssey in lysosomal storage disorders: parents using internet search engines as an efficient diagnostic strategy in rare diseases. Arch. Dis. Child. 95(8), 642–644 (2010)CrossRefGoogle Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Radu Dragusin
    • 1
  • Paula Petcu
    • 1
  • Christina Lioma
    • 2
  • Birger Larsen
    • 3
  • Henrik Jørgensen
    • 4
  • Ole Winther
    • 5
  1. 1.Computer ScienceUniversity of CopenhagenCopenhagenDenmark
  2. 2.InformaticsStuttgart UniversityStuttgartGermany
  3. 3.Royal School of Library and Information ScienceCopenhagenDenmark
  4. 4.Department of Clinical BiochemistryBispebjerg HospitalCopenhagenDenmark
  5. 5.InformaticsTechnical University of DenmarkLyngbyDenmark

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