Querying Across Genres for Medical Claims in News
Chaoyuan Zuo, Narayan Acharya, Ritwik Banerjee · 2020
We present a query-based biomedical information retrieval task across two vastly different genres -newswire and research literaturewhere the goal is to find the research publication that supports the primary claim made in a health-related news article.For this task, we present a new dataset of 5,034 claims from news paired with research abstracts.Our approach consists of two steps: (i) selecting the most relevant candidates from a collection of 222k research abstracts, and (ii) re-ranking this list.We compare the classical IR approach using BM25 with more recent transformerbased models.Our results show that crossgenre medical IR is a viable task, but incorporating domain-specific knowledge is crucial.