output
20162023
most citedA Study of Generative Large Language Model for Medical Research and Healthcare

400 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2023Show all

4 papers · 1 filter

cs.CL2023★ 71 cited

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…

cs.CL2023★ 400 cited

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…

cs.CL2023★ 30 cited

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…

cs.CL2023★ 40 cited

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…