Explorers at #SMM4H 2023: Enhancing BERT for Health Applications through
  Knowledge and Model Fusion
Xutong Yue Xilai Wang Yuxin He Zhenkun Zhou
An increasing number of individuals are willing to post states and opinions
in social media, which has become a valuable data resource for studying human
health. Furthermore, social media has been a crucial research point for
healthcare now. This paper outlines the methods in our participation in the
#SMM4H 2023 Shared Tasks, including data preprocessing, continual pre-training
and fine-tuned optimization strategies. Especially for the Named Entity
Recognition (NER) task, we utilize the model architecture named W2NER that
effectively enhances the model generalization ability. Our method achieved
first place in the Task 3. This paper has been peer-reviewed and accepted for
presentation at the #SMM4H 2023 Workshop.