  Background: The web has become a primary information resource about illnesses
and treatments for both medical and non-medical users. Standard web search is
by far the most common interface for such information. It is therefore of
interest to find out how well web search engines work for diagnostic queries
and what factors contribute to successes and failures. Among diseases, rare (or
orphan) diseases represent an especially challenging and thus interesting class
to diagnose as each is rare, diverse in symptoms and usually has scattered
resources associated with it. Methods: We use an evaluation approach for web
search engines for rare disease diagnosis which includes 56 real life
diagnostic cases, state-of-the-art evaluation measures, and curated information
resources. In addition, we introduce FindZebra, a specialized (vertical) rare
disease search engine. FindZebra is powered by open source search technology
and uses curated freely available online medical information. Results:
FindZebra outperforms Google Search in both default setup and customised to the
resources used by FindZebra. We extend FindZebra with specialized
functionalities exploiting medical ontological information and UMLS medical
concepts to demonstrate different ways of displaying the retrieved results to
medical experts. Conclusions: Our results indicate that a specialized search
engine can improve the diagnostic quality without compromising the ease of use
of the currently widely popular web search engines. The proposed evaluation
approach can be valuable for future development and benchmarking. The FindZebra
search engine is available at http://www.findzebra.com/.
