Diagnose This If You Can

On the Effectiveness of Search Engines in Finding Medical Self-diagnosis Information
  • Guido Zuccon
  • Bevan Koopman
  • João Palotti
Conference paper

DOI: 10.1007/978-3-319-16354-3_62

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9022)
Cite this paper as:
Zuccon G., Koopman B., Palotti J. (2015) Diagnose This If You Can. In: Hanbury A., Kazai G., Rauber A., Fuhr N. (eds) Advances in Information Retrieval. ECIR 2015. Lecture Notes in Computer Science, vol 9022. Springer, Cham


An increasing amount of people seek health advice on the web using search engines; this poses challenging problems for current search technologies. In this paper we report an initial study of the effectiveness of current search engines in retrieving relevant information for diagnostic medical circumlocutory queries, i.e., queries that are issued by people seeking information about their health condition using a description of the symptoms they observes (e.g. hives all over body) rather than the medical term (e.g. urticaria). This type of queries frequently happens when people are unfamiliar with a domain or language and they are common among health information seekers attempting to self-diagnose or self-treat themselves. Our analysis reveals that current search engines are not equipped to effectively satisfy such information needs; this can have potential harmful outcomes on people’s health. Our results advocate for more research in developing information retrieval methods to support such complex information needs.


Medical Information Retrieval Self-Diagnosis Evaluation Medical Circumlocution 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Guido Zuccon
    • 1
  • Bevan Koopman
    • 2
  • João Palotti
    • 3
  1. 1.Queensland University of TechnologyBrisbaneAustralia
  2. 2.Australian e-Health Research Centre, CSIROBrisbaneAustralia
  3. 3.Vienna University of TechnologyViennaAustria

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