Improving large language models for clinical named entity recognition via prompt engineering

Y Hu, Q Chen, J Du, X Peng, VK Keloth… - Journal of the …, 2024 - academic.oup.com
Importance The study highlights the potential of large language models, specifically GPT-3.5
and GPT-4, in processing complex clinical data and extracting meaningful information with …

[HTML][HTML] An empirical evaluation of prompting strategies for large language models in zero-shot clinical natural language processing: algorithm development and …

S Sivarajkumar, M Kelley… - JMIR Medical …, 2024 - medinform.jmir.org
Background Large language models (LLMs) have shown remarkable capabilities in natural
language processing (NLP), especially in domains where labeled data are scarce or …

Enhancing early detection of cognitive decline in the elderly: a comparative study utilizing large language models in clinical notes

X Du, J Novoa-Laurentiev, JM Plasek, YW Chuang… - …, 2024 - thelancet.com
Summary Background Large language models (LLMs) have shown promising performance
in various healthcare domains, but their effectiveness in identifying specific clinical …

Advancing entity recognition in biomedicine via instruction tuning of large language models

VK Keloth, Y Hu, Q **e, X Peng, Y Wang… - …, 2024 - academic.oup.com
Abstract Motivation Large Language Models (LLMs) have the potential to revolutionize the
field of Natural Language Processing, excelling not only in text generation and reasoning …

Integrating deep learning architectures for enhanced biomedical relation extraction: a pipeline approach

MJ Sarol, G Hong, E Guerra, H Kilicoglu - Database, 2024 - academic.oup.com
Biomedical relation extraction from scientific publications is a key task in biomedical natural
language processing (NLP) and can facilitate the creation of large knowledge bases, enable …

A comparative study of large language model-based zero-shot inference and task-specific supervised classification of breast cancer pathology reports

M Sushil, T Zack, D Mandair, Z Zheng… - Journal of the …, 2024 - academic.oup.com
Objective Although supervised machine learning is popular for information extraction from
clinical notes, creating large annotated datasets requires extensive domain expertise and is …

[HTML][HTML] The Clinicians' Guide to Large Language Models: A General Perspective With a Focus on Hallucinations

D Roustan, F Bastardot - Interactive journal of medical research, 2025 - i-jmr.org
Large language models (LLMs) are artificial intelligence tools that have the prospect of
profoundly changing how we practice all aspects of medicine. Considering the incredible …