PDF] Mining and Ranking Biomedical Synonym Candidates from

The results show that PRF-based reranking outperformed word embedding based approach and a strong baseline using interwiki link frequency, and suggests that medical synonyms mined from Wikipedia can increase the coverage of existing synonym resources such as UMLS. Biomedical synonyms are important resources for Natural Language Processing in Biomedical domain. Existing synonym resources (e.g., the UMLS) are not complete. Manual efforts for expanding and enriching these resources are prohibitively expensive. We therefore develop and evaluate approaches for automated synonym extraction from Wikipedia. Using the inter-wiki links, we extracted the candidate synonyms (anchor-text e.g., “increased thirst”) in a Wikipedia page and the title (e.g., “polyuria”) of its corresponding linked page. We rank synonym candidates with word embedding and pseudo-relevance feedback (PRF). Our results show that PRF-based reranking outperformed word embedding based approach and a strong baseline using interwiki link frequency. A hybrid method, Rank Score Combination, achieved the best results. Our analysis also suggests that medical synonyms mined from Wikipedia can increase the coverage of existing synonym resources such as UMLS.

An overview of biomedical entity linking throughout the years

NLM-Chem, a new resource for chemical entity recognition in PubMed

Data Mining in Biomedicine: Current Applications and Further

Are We There Yet? A Roadmap of Network Visualization from Surveys

Frontiers An advanced systems biology framework of feature

AMMU: A survey of transformer-based biomedical pretrained language

Pharmaceutics Announcements

Minerals, Free Full-Text

Biomedical discovery through the integrative biomedical knowledge

Nutrients, Free Full-Text

Graph representation learning in biomedicine and healthcare