Give It a Shot: Few-shot Learning to Normalize ADR Mentions in Social Media Posts
Emmanouil Manousogiannis, Sepideh Mesbah, Alessandro Bozzon, Selene Baez Santamaria, Robert Jan Sips
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-the art 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.- Anthology ID:
- W19-3219
- Volume:
- Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Davy Weissenbacher, Graciela Gonzalez-Hernandez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 114–116
- Language:
- URL:
- https://aclanthology.org/W19-3219
- DOI:
- 10.18653/v1/W19-3219
- Cite (ACL):
- Emmanouil Manousogiannis, Sepideh Mesbah, Alessandro Bozzon, Selene Baez Santamaria, and Robert Jan Sips. 2019. Give It a Shot: Few-shot Learning to Normalize ADR Mentions in Social Media Posts. In Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task, pages 114–116, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Give It a Shot: Few-shot Learning to Normalize ADR Mentions in Social Media Posts (Manousogiannis et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/W19-3219.pdf
- Data
- SMM4H