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Knowledge-Enhanced information Extraction across languages for PHArmacovigilance

  • Duration:

KEEPHA is a trilateral DFG Project, together with partners from France (LIMSI/LISN) and Japan (NAIST, NII, RIKEN). The present project aims to design Artificial Intelligence (AI) methods that automatically digest these different types of text sources and jointly extract such knowledge and observations in order to populate existing knowledge bases. Our project showcases these methods in the domain of pharmacovigilance, which endeavors to maintain up-to-date knowledge on adverse drug reactions (ADRs) for the benefit of public health. In this domain, authoritative sources include scientific journals and drug labels while elementary observations are reported in patient records and social media.




DFG - German Research Foundation

DFG - German Research Foundation

Publications about the project

Davy Weissenbacher; Karen O'Connor; Siddharth Rawal; Yu Zhang; Richard Tzong-Han Tsai; Timothy Miller; Dongfang Xu; Carol Anderson; Bo Liu; Qing Han; Jinfeng Zhang; Igor Kulev; Berkay Köprü; Raul Rodriguez-Esteban; Elif Ozkirimli; Ammer Ayach; Roland Roller; Stephen Piccolo; Peijin Han; V G Vinod Vydiswaran; Ramya Tekumalla; Juan M Banda; Parsa Bagherzadeh; Sabine Bergler; João F Silva; Tiago Almeida; Paloma Martinez; Renzo Rivera-Zavala; Chen-Kai Wang; Hong-Jie Dai; Luis Alberto Robles Hernandez; Graciela Gonzalez-Hernandez

In: Database - The Journal of Biological Databases and Curation, Vol. 2023, Pages 1-10, Oxford University Press, 2/2023.

To the publication

Lisa Raithel; Philippe Thomas; Roland Roller; Oliver Sapina; Sebastian Möller; Pierre Zweigenbaum

In: Proceedings of the 13th Conference on Language Resources and Evaluation. International Conference on Language Resources and Evaluation (LREC-2022), June 20-25, Marseille, France, Pages 3637-3649, European Language Resources Association, 2022.

To the publication