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1.
Front Digit Health ; 5: 1142897, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-36866107
2.
Int J Med Inform ; 82(6): 528-38, 2013 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-23462700

RESUMEN

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/.


Asunto(s)
Información de Salud al Consumidor/normas , Conocimientos, Actitudes y Práctica en Salud , Informática Médica , Enfermedades Raras , Motor de Búsqueda/estadística & datos numéricos , Humanos , Internet
3.
Rare Dis ; 1: e25001, 2013.
Artículo en Inglés | MEDLINE | ID: mdl-25002998

RESUMEN

In our recent paper, we study web search as an aid in the process of diagnosing rare diseases. To answer the question of how well Google Search and PubMed perform, we created an evaluation framework with 56 diagnostic cases and made our own specialized search engine, FindZebra (findzebra.com). FindZebra uses a set of publicly available curated sources on rare diseases and an open-source information retrieval system, Indri. Our evaluation and the feedback received after the publication of our paper both show that FindZebra outperforms Google Search and PubMed. In this paper, we summarize the original findings and the response to FindZebra, discuss why Google Search is not designed for specialized tasks and outline some of the current trends in using web resources and social media for medical diagnosis.

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