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Project | KEEPHA

Duration:

Knowledge-Enhanced information Extraction across languages for PHArmacovigilance

Application fields

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.

Partners

DFKI, LIMSI/LISN, NAIST, NII, RIKEN

Publications about the project

  1. Overview of #SMM4H 2024 -- Task 2: Cross-Lingual Few-Shot Relation Extraction for Pharmacovigilance in French, German, and Japanese

    Lisa Raithel; Philippe Thomas; Bhuvanesh Verma; Roland Roller; Hui-Syuan Yeh; Shuntaro Yada; Cyril Grouin; Shoko Wakamiya; Eiji Aramaki; Sebastian Möller; Pierre Zweigenbaum

    In: Dongfang Xu; Graciela Gonzalez-Hernandez (Hrsg.). Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks. Social Media Mining for Health Research and Applications Workshop (SMM4H-2024), located at ACL 2024, August 15, Bangkok, Thailand, Pages 170-182, Association for Computational Linguistics, 2024.

Sponsors

DFG - German Research Foundation

DFG - German Research Foundation