FindZebra: A search engine for rare diseases
Radu Dragusin (1, 2), Paula Petcu (1, 3), Christina Lioma (1 and, 2), Birger Larsen (4), Henrik L. J{\o}rgensen (5), Ingemar J. Cox (1, 6),, Lars Kai Hansen (1), Peter Ingwersen (4), Ole Winther (1) ((1) DTU Compute,, Technical University of Denmark, Denmark

TL;DR
FindZebra is a specialized search engine for rare diseases that outperforms general search engines like Google in diagnostic accuracy by leveraging curated medical information and ontological data.
Contribution
The paper introduces FindZebra, a novel vertical search engine for rare diseases, and presents an evaluation approach demonstrating its superior diagnostic performance.
Findings
FindZebra outperforms Google Search in diagnostic accuracy.
Specialized functionalities improve result relevance for medical experts.
Evaluation method aids future development and benchmarking of medical search engines.
Abstract
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…
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