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 · 2019
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.