DKE-Research at SemEval-2024 Task 2: Incorporating Data Augmentation with Generative Models and Biomedical Knowledge to Enhance Inference Robustness

no code implementations • 14 Apr 2024 • Yuqi Wang, Zeqiang Wang, Wei Wang, Qi Chen, Kaizhu Huang, Anh Nguyen, Suparna De

Safe and reliable natural language inference is critical for extracting insights from clinical trial reports but poses challenges due to biases in large pre-trained language models.

Data Augmentation Multi-Task Learning +2

Zero-Shot Medical Information Retrieval via Knowledge Graph Embedding

no code implementations • 31 Oct 2023 • Yuqi Wang, Zeqiang Wang, Wei Wang, Qi Chen, Kaizhu Huang, Anh Nguyen, Suparna De

In the era of the Internet of Things (IoT), the retrieval of relevant medical information has become essential for efficient clinical decision-making.

Decision Making Information Retrieval +2

YATO: Yet Another deep learning based Text analysis Open toolkit

1 code implementation • 28 Sep 2022 • Zeqiang Wang, Yile Wang, Jiageng Wu, Zhiyang Teng, Jie Yang

Designed in a hierarchical structure, YATO supports free combinations of three types of widely used features including 1) traditional neural networks (CNN, RNN, etc.

METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets

1 code implementation • 28 Sep 2022 • Peilin Zhou, Zeqiang Wang, Dading Chong, Zhijiang Guo, Yining Hua, Zichang Su, Zhiyang Teng, Jiageng Wu, Jie Yang

To further investigate tweet users' attitudes toward specific entities, 4 types of entities (Person, Organization, Drug, and Vaccine) are selected and annotated with user sentiments, resulting in a targeted sentiment dataset with 9, 101 entities (in 5, 278 tweets).

Epidemiology named-entity-recognition +3