Rare disease diagnosis as an information retrieval task

  • Authors:

  • Radu Dragusin;Paula Petcu;Christina Lioma;Birger Larsen;Henrik Jørgensen;Ole Winther

  • Affiliations:

  • Computer Science, University of Copenhagen, Copenhagen, Denmark;Computer Science, University of Copenhagen, Copenhagen, Denmark;Informatics, Stuttgart University, Stuttgart, Germany;Royal School of Library and Information Science, Copenhagen, Denmark;Department of Clinical Biochemistry, Bispebjerg Hospital, Copenhagen, Denmark;Informatics, Technical University of Denmark, Lyngby, Denmark

  • Venue:
  • ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
  • Year:
  • 2011

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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.