Maria-Dorinela Sîrbu


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Building a Comprehensive Romanian Knowledge Base for Drug Administration
Bogdan Nicula | Mihai Dascalu | Maria-Dorinela Sîrbu | Ștefan Trăușan-Matu | Alexandru Nuță
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)

Information on drug administration is obtained traditionally from doctors and pharmacists, as well as leaflets which provide in most cases cumbersome and hard-to-follow details. Thus, the need for medical knowledge bases emerges to provide access to concrete and well-structured information which can play an important role in informing patients. This paper introduces a Romanian medical knowledge base focused on drug-drug interactions, on representing relevant drug information, and on symptom-disease relations. The knowledge base was created by extracting and transforming information using Natural Language Processing techniques from both structured and unstructured sources, together with manual annotations. The resulting Romanian ontologies are aligned with larger English medical ontologies. Our knowledge base supports queries regarding drugs (e.g., active ingredients, concentration, expiration date), drug-drug interaction, symptom-disease relations, as well as drug-symptom relations.