68 citations · 121 across the 4 of their papers we have counts for
4 papers
Information Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models?
Yan Hu, Xu Zuo, Yujia Zhou +9
Backgrounds: Information extraction (IE) is critical in clinical natural language processing (NLP). While large language models (LLMs) excel on generative tasks, their performance…
Improving Entity Recognition Using Ensembles of Deep Learning and Fine-tuned Large Language Models: A Case Study on Adverse Event Extraction from Multiple Sources
Yiming Li, Deepthi Viswaroopan, William He +4
Adverse event (AE) extraction following COVID-19 vaccines from text data is crucial for monitoring and analyzing the safety profiles of immunizations. Traditional deep learning mod…
Relation Extraction Using Large Language Models: A Case Study on Acupuncture Point Locations
Yiming Li, Xueqing Peng, Jianfu Li +6
In acupuncture therapy, the accurate location of acupoints is essential for its effectiveness. The advanced language understanding capabilities of large language models (LLMs) like…
Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering
Yan Hu, Qingyu Chen, Jingcheng Du +9
Objective: This study quantifies the capabilities of GPT-3.5 and GPT-4 for clinical named entity recognition (NER) tasks and proposes task-specific prompts to improve their perform…