22 citations · 37 across the 10 of their papers we have counts for
10 papers
Retrieval augmented generation based dynamic prompting for few-shot biomedical named entity recognition using large language models
Yao Ge, Sudeshna Das, Yuting Guo +1
Biomedical named entity recognition (NER) is a high-utility natural language processing (NLP) task, and large language models (LLMs) show promise particularly in few-shot settings…
Leveraging large language models and traditional machine learning ensembles for ADHD detection from narrative transcripts
Yuxin Zhu, Yuting Guo, Noah Marchuck +2
Despite rapid advances in large language models (LLMs), their integration with traditional supervised machine learning (ML) techniques that have proven applicability to medical dat…
HILGEN: Hierarchically-Informed Data Generation for Biomedical NER Using Knowledgebases and Large Language Models
Yao Ge, Yuting Guo, Sudeshna Das +3
We present HILGEN, a Hierarchically-Informed Data Generation approach that combines domain knowledge from the Unified Medical Language System (UMLS) with synthetic data generated b…
Benchmarking Open-Source Large Language Models on Healthcare Text Classification Tasks
Yuting Guo, Abeed Sarker
The application of large language models (LLMs) to healthcare information extraction has emerged as a promising approach. This study evaluates the classification performance of fiv…
Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study
Sudeshna Das, Yao Ge, Yuting Guo +19
The increasing use of social media to share lived and living experiences of substance use presents a unique opportunity to obtain information on side effects, use patterns, and opi…
Evaluating Large Language Models for Health-Related Text Classification Tasks with Public Social Media Data
Yuting Guo, Anthony Ovadje, Mohammed Ali Al-Garadi +1
Large language models (LLMs) have demonstrated remarkable success in NLP tasks. However, there is a paucity of studies that attempt to evaluate their performances on social media-b…
Leveraging Few-Shot Learning and Large Language Models for Analyzing Blood Pressure Variations Across Biological Sex from Scientific Literature
Yuting Guo, Seyedeh Somayyeh Mousavi, Reza Sameni +1
Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often without adjusting BP readings for ind…
Learning from Two Decades of Blood Pressure Data: Demography-Specific Patterns Across 75 Million Patient Encounters
Seyedeh Somayyeh Mousavi, Yuting Guo, Abeed Sarker +1
Hypertension is a global health concern with an increasing prevalence, underscoring the need for effective monitoring and analysis of blood pressure (BP) dynamics. We analyzed a su…
Generalizable Natural Language Processing Framework for Migraine Reporting from Social Media
Yuting Guo, Swati Rajwal, Sahithi Lakamana +10
Migraine is a high-prevalence and disabling neurological disorder. However, information migraine management in real-world settings could be limited to traditional health informatio…
Few-shot learning for medical text: A systematic review
Yao Ge, Yuting Guo, Yuan-Chi Yang +2
Objective: Few-shot learning (FSL) methods require small numbers of labeled instances for training. As many medical topics have limited annotated textual data in practical settings…