400 citations
5 papers
Model Tuning or Prompt Tuning? A Study of Large Language Models for Clinical Concept and Relation Extraction
Cheng Peng, Xi Yang, Kaleb E Smith +4
Objective To develop soft prompt-based learning algorithms for large language models (LLMs), examine the shape of prompts, prompt-tuning using frozen/unfrozen LLMs, transfer learni…
A Study of Generative Large Language Model for Medical Research and Healthcare
Cheng Peng, Xi Yang, Aokun Chen +16
There is enormous enthusiasm and concerns in using large language models (LLMs) in healthcare, yet current assumptions are all based on general-purpose LLMs such as ChatGPT. This s…
Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension
Cheng Peng, Xi Yang, Zehao Yu +3
Objective: To develop a natural language processing system that solves both clinical concept extraction and relation extraction in a unified prompt-based machine reading comprehens…
Contextualized Medication Information Extraction Using Transformer-based Deep Learning Architectures
Aokun Chen, Zehao Yu, Xi Yang +3
Objective: To develop a natural language processing (NLP) system to extract medications and contextual information that help understand drug changes. This project is part of the 20…
SODA: A Natural Language Processing Package to Extract Social Determinants of Health for Cancer Studies
Zehao Yu, Xi Yang, Chong Dang +12
Objective: We aim to develop an open-source natural language processing (NLP) package, SODA (i.e., SOcial DeterminAnts), with pre-trained transformer models to extract social deter…