1.7k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of FloridaUS30 papers
- UF Health Cancer Center5 papers
- Cornell UniversityUS4 papers
- Florida CollegeUS4 papers
- Northwestern UniversityUS4 papers
- Stanford UniversityUS4 papers
- Weill Cornell MedicineUS4 papers
- Florida State UniversityUS3 papers
- University of Alabama at BirminghamUS3 papers
- University of California, Los AngelesUS3 papers
- University of California San DiegoUS3 papers
- University of MichiganUS3 papers
7 papers · 1 filter
Automatic Summarization of Doctor-Patient Encounter Dialogues Using Large Language Model through Prompt Tuning
Mengxian Lyu, Cheng Peng, Xiaohan Li +3
Automatic text summarization (ATS) is an emerging technology to assist clinicians in providing continuous and coordinated care. This study presents an approach to summarize doctor-…
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…
A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Models
Zehao Yu, Xi Yang, Chong Dang +8
Social and behavioral determinants of health (SBDoH) have important roles in shaping people's health. In clinical research studies, especially comparative effectiveness studies, fa…