400 citations · 645 across the 20 of their papers we have counts for
9 papers · 1 filter
UF-HOBI at "Discharge Me!": A Hybrid Solution for Discharge Summary Generation Through Prompt-based Tuning of GatorTronGPT Models
Mengxian Lyu, Cheng Peng, Daniel Paredes +4
Automatic generation of discharge summaries presents significant challenges due to the length of clinical documentation, the dispersed nature of patient information, and the divers…
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
Lu Li, Tianyu Zhang, Zhiqi Bu +7
Model merging has emerged as an effective approach to combine multiple single-task models into a multitask model. This process typically involves computing a weighted average of th…
Use of natural language processing to extract and classify papillary thyroid cancer features from surgical pathology reports
Ricardo Loor-Torres, Yuqi Wu, Esteban Cabezas +10
Background We aim to use Natural Language Processing (NLP) to automate the extraction and classification of thyroid cancer risk factors from pathology reports. Methods We analyzed…
Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding
Ahmad Idrissi-Yaghir, Amin Dada, Henning Schäfer +17
Recent advances in natural language processing (NLP) can be largely attributed to the advent of pre-trained language models such as BERT and RoBERTa. While these models demonstrate…
Improving Generalizability of Extracting Social Determinants of Health Using Large Language Models through Prompt-tuning
Cheng Peng, Zehao Yu, Kaleb E Smith +3
The progress in natural language processing (NLP) using large language models (LLMs) has greatly improved patient information extraction from clinical narratives. However, most met…
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-…
Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure
Ziyi Chen, Mengyuan Zhang, Mustafa Mohammed Ahmed +4
Cancer treatments are known to introduce cardiotoxicity, negatively impacting outcomes and survivorship. Identifying cancer patients at risk of heart failure (HF) is critical to im…
Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data
Aokun Chen, Qian Li, Yu Huang +7
A comprehensive view of factors associated with AD/ADRD will significantly aid in studies to develop new treatments for AD/ADRD and identify high-risk populations and patients for…
Me LLaMA: Foundation Large Language Models for Medical Applications
Qianqian Xie, Qingyu Chen, Aokun Chen +15
Recent advancements in large language models (LLMs) like ChatGPT and LLaMA show promise in medical applications, yet challenges remain in medical language comprehension. This study…