Reranking for a Polish Medical Search Engine

Healthcare professionals are often overworked, which may impair their efficacy. Text search engines may facilitate their work. However, before making health decisions, it is important for a medical professional to consult verified sources rather than unknown web pages. In this work, we present our approach for creating a text search engine based on verified resources in the Polish language, dedicated to medical workers. This consists of collecting and comprehensively analyzing texts annotated by medical professionals and evaluating various neural reranking models. During the annotation process, we differentiate between an abstract information need and a search query. Our study shows that even within a group of trained medical specialists there is extensive disagreement on the relevance of a document to the information need. We prove that available multilingual rerankers trained in the zero-shot setup are effective for the Polish language in searches initiated by both natural language expressions and keyword search queries.

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1. Main Track Short Papers

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2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).