Biomedical NLP

Our work in biomedical and clinical NLP includes developing a biomedical QA system, drug-drug interaction extraction from biomedical literature, topical phrase extraction from clinical reports, understanding patient reviews and adverse drug reaction detection in social media.

Participants

Lin Gui, Gabriele Pergola

Project

• DeepPatient - Deep Understanding of Patient Experience of Healthcare from Social Media

Publications

• L. Gui and Y. He. Understanding Patient Reviews with Minimum Supervision, Artificial Intelligence in Medicine, to appear.
• G. Pergola, E. Kochkina, L. Gui, M. Liakata and Y. He. Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies, The 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL), Apr. 2021.
• D. Zhou, L Miao and Y. He. Position-Aware Deep Multi-Task Learning for Drug-Drug Interaction Extraction. Artificial Intelligence in Medicine, 87:1-8, 2018.
• G. Pergola, Y. He and D. Lowe. Topical Phrase Extraction from Clinical Reports by Incorporating both Local and Global Context, The 2nd AAAI Workshop on Health Intelligence, New Orleans, Louisiana, USA, Feb. 2018.
• T. Huynh, Y. He, A. Willis and S. Rueger. Adverse Drug Reaction Classification With Deep Neural Networks, The 26th International Conference on Computational Linguistics (COLING), Osaka, Japan, Dec. 2016.
• Y. He. Extracting Topical Phrases from Clinical Documents. The 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona, USA, Feb. 2016.