Give It a Shot: Few-shot Learning to Normalize ADR Mentions in Social Media Posts
Emmanouil Manousogiannis, Sepideh Mesbah, Alessandro Bozzon, Selene Baez, 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
- 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, 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/ingestion-script-update/W19-3219.pdf
- Data
- SMM4H