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FindZebra: a search engine for rare diseases.

Radu Dragusin1, Paula Petcu, Christina Lioma

  • 1DTU Compute, Technical University of Denmark, Denmark. raddr@imm.dtu.dk

International Journal of Medical Informatics
|March 7, 2013
PubMed
Summary

A specialized search engine, FindZebra, improves rare disease diagnosis compared to standard web search. This approach enhances diagnostic quality without sacrificing user-friendliness, offering a valuable tool for medical professionals.

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Area of Science:

  • Medical Informatics
  • Bioinformatics
  • Computational Biology

Background:

  • The internet is a key resource for health information, with web search as the primary access method.
  • Diagnosing rare diseases presents challenges due to symptom diversity and scattered information.
  • Evaluating web search engine performance for rare disease diagnostics is crucial.

Purpose of the Study:

  • To evaluate web search engines for rare disease diagnosis.
  • To introduce and assess FindZebra, a specialized search engine for rare diseases.
  • To develop an evaluation framework for rare disease diagnostic search tools.

Main Methods:

  • An evaluation approach using 56 real diagnostic cases was designed.
  • Google Search was customized, and a specialized rare disease search engine, FindZebra, was developed.
  • FindZebra utilizes open-source technology and curated online medical information.

Main Results:

  • FindZebra outperformed Google Search in diagnostic accuracy, both in default and customized settings.
  • Specialized functionalities were added to FindZebra, leveraging medical ontologies and UMLS concepts.
  • Methods for displaying retrieved results to medical experts were demonstrated.

Conclusions:

  • Specialized search engines can enhance diagnostic quality for rare diseases.
  • FindZebra offers improved diagnostic capabilities without compromising ease of use.
  • The evaluation approach provides a benchmark for future search engine development.