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NTCIR-17 MedNLP-SC Social Media Adverse Drug Event Detection: Subtask Overview

Shoko Wakamiya; Lis Kanashiro Pereira; Lisa Raithel; Hui-Syuan Yeh; Peitao Han; Seiji Shimizu; Tomohiro Nishiyama; Gabriel Herman Bernardim Andrade; Noriki Nishida; Hiroki Teranishi; Narumi Tokunaga; Philippe Thomas; Roland Roller; Pierre Zweigenbaum; Yuji Matsumoto; Akiko Aizawa; Sebastian Möller; Cyril Grouin; Thomas Lavergne; Aurélie Névéol; Patrick Paroubek; Shuntaro Yada; Eiji Aramaki
In: The 17th NTCIR Conference - Evaluation of Information Access Technologies. Conference on Evaluation of Information Access Technologies (NTCIR-17), December 12-15, Tokyo, Japan, National Institute of Informatics (NII), 2023.


This paper presents the Social Media Adverse Drug Event Detection (SM-ADE) subtask as part of the shared task Medical Natural Language Processing for Social Media and Clinical Texts (MedNLP-SC) at NTCIR-17. The SM-ADE subtask aims to identify a set of symptoms caused by a drug, referred to as adverse drug event (ADE) detection, within social media texts in multiple languages, including Japanese, English, French, and German. The competition attracted 26 teams, of which eight submitted official runs for the SM-ADE subtask. We believe this task will be essential to develop core technologies of practical medical applications in the near future.