Give it a shot: Few-shot learning to normalize ADR mentions in Social Media posts

E. Manousogiannis, Sepideh Mesbah, Selene Baez Santamaria, Alessandro Bozzon, Robert-Jan Sips

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Abstract

This paper describes the system that team MYTOMORROWS-TU DELFT developed for the 2019 Social Media Mining for Health Applications (SMM4H) Shared Task 3, for the end-to-end normalization of ADR tweet mentions to their corresponding MEDDRA codes. For the first two steps, we reuse a state-of-theart approach, focusing our contribution on the final entity-linking step. For that we propose a simple Few-Shot learning approach, based on pre-trained word embeddings and data from the UMLS, combined with the provided training data. Our system (relaxed F1: 0.337- 0.345) outperforms the average (relaxed F1 0.2972) of the participants in this task, demonstrating the potential feasibility of few-shot learning in the context of medical text normalization.
Original languageEnglish
Title of host publicationProceedings of the 4th Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task
EditorsDavy Weissenbacher, Graciela Gonzalez-Hernandez
PublisherAssociation for Computational Linguistics
Pages114–116
Number of pages4
ISBN (Electronic)978-1-950737-46-8
Publication statusPublished - 2019
Event4th Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task - Florence, Italy
Duration: 2 Aug 20192 Aug 2019
Conference number: 4
https://www.aclweb.org/anthology/W19-32

Conference

Conference4th Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task
Abbreviated title#SMM4H
CountryItaly
CityFlorence
Period2/08/192/08/19
Internet address

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  • Cite this

    Manousogiannis, E., Mesbah, S., Baez Santamaria, S., Bozzon, A., & Sips, R-J. (2019). Give it a shot: Few-shot learning to normalize ADR mentions in Social Media posts. In D. Weissenbacher, & G. Gonzalez-Hernandez (Eds.), Proceedings of the 4th Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task (pp. 114–116). Association for Computational Linguistics.