Abstract
Clinical Natural Language Processing has been an increasingly popular research area in the NLP community. With the rise of large language models (LLMs) and their impressive abilities in NLP tasks, it is crucial to pay attention to their clinical applications. Sequence to sequence generative approaches with LLMs have been widely used in recent years. To be a part of the research in clinical NLP with recent advances in the field, we participated in task A of MEDIQA-Chat at ACL-ClinicalNLP Workshop 2023. In this paper, we explain our methods and findings as well as our comments on our results and limitations.- Anthology ID:
- 2023.clinicalnlp-1.19
- Volume:
- Proceedings of the 5th Clinical Natural Language Processing Workshop
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Venue:
- ClinicalNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 144–149
- Language:
- URL:
- https://aclanthology.org/2023.clinicalnlp-1.19
- DOI:
- 10.18653/v1/2023.clinicalnlp-1.19
- Cite (ACL):
- Kadir Bulut Ozler and Steven Bethard. 2023. clulab at MEDIQA-Chat 2023: Summarization and classification of medical dialogues. In Proceedings of the 5th Clinical Natural Language Processing Workshop, pages 144–149, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- clulab at MEDIQA-Chat 2023: Summarization and classification of medical dialogues (Ozler & Bethard, ClinicalNLP 2023)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2023.clinicalnlp-1.19.pdf