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cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

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…

cs.CL2024

Social Media as a Sensor: Analyzing Twitter Data for Breast Cancer Medication Effects Using Natural Language Processing

Seibi Kobara, Alireza Rafiei, Masoud Nateghi +3

Breast cancer is a significant public health concern and is the leading cause of cancer-related deaths among women. Despite advances in breast cancer treatments, medication non-adh…

cs.CL2024

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…