Building a Comprehensive Romanian Knowledge Base for Drug Administration

Bogdan Nicula, Mihai Dascalu, Maria-Dorinela Sîrbu, Ștefan Trăușan-Matu, Alexandru Nuță

Abstract
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.
Anthology ID:
R19-1096
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
829–836
Language:
URL:
https://aclanthology.org/R19-1096
DOI:
10.26615/978-954-452-056-4_096
Bibkey:
Cite (ACL):
Bogdan Nicula, Mihai Dascalu, Maria-Dorinela Sîrbu, Ștefan Trăușan-Matu, and Alexandru Nuță. 2019. Building a Comprehensive Romanian Knowledge Base for Drug Administration. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 829–836, Varna, Bulgaria. INCOMA Ltd..
Cite (Informal):
Building a Comprehensive Romanian Knowledge Base for Drug Administration (Nicula et al., RANLP 2019)
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PDF:
https://preview.aclanthology.org/nschneid-patch-3/R19-1096.pdf
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