TY - JOUR
T1 - FindZebra
T2 - a search engine for rare diseases
AU - Dragusin, Radu
AU - Petcu, Paula
AU - Lioma, Christina
AU - Larsen, Birger
AU - Jørgensen, Henrik L.
AU - Cox, Ingemar
AU - Hansen, Lars Kai
AU - Ingwersen, Peter
AU - Christensen, Ole Winther
PY - 2013
Y1 - 2013
N2 - 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 to this 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 design an evaluation approach for web search engines for rare disease diagnosis which includes 56 real life diagnostic cases, performance measures, information resources and guidelines for customising Google Search to this task. 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 set-up 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 standard web search. The proposed evaluation approach can be valuable for future development and benchmarking. The FindZebra search engine is available at http://www.findzebra.com/.
AB - 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 to this 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 design an evaluation approach for web search engines for rare disease diagnosis which includes 56 real life diagnostic cases, performance measures, information resources and guidelines for customising Google Search to this task. 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 set-up 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 standard web search. The proposed evaluation approach can be valuable for future development and benchmarking. The FindZebra search engine is available at http://www.findzebra.com/.
UR - http://www.scopus.com/inward/record.url?scp=84874015081&partnerID=8YFLogxK
U2 - 10.1016/j.ijmedinf.2013.01.005
DO - 10.1016/j.ijmedinf.2013.01.005
M3 - Journal article
AN - SCOPUS:84891650295
SN - 1386-5056
VL - 82
SP - 528
EP - 538
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
IS - 6
ER -