Large language models in biomedicine and health: current research landscape and future directions

Z Lu, Y Peng, T Cohen, M Ghassemi… - Journal of the …, 2024 - academic.oup.com
Large language models (LLMs) are a specialized type of generative artificial intelligence (AI)
focused on generating natural language text. These models are developed through …

Harnessing large language models' zero-shot and few-shot learning capabilities for regulatory research

H Meshkin, J Zirkle, G Arabidarrehdor… - Briefings in …, 2024 - academic.oup.com
Large language models (LLMs) are sophisticated AI-driven models trained on vast sources
of natural language data. They are adept at generating responses that closely mimic human …

Language models for data extraction and risk of bias assessment in complementary medicine

H Lai, J Liu, C Bai, H Liu, B Pan, X Luo, L Hou… - npj Digital …, 2025 - nature.com
Large language models (LLMs) have the potential to enhance evidence synthesis efficiency
and accuracy. This study assessed LLM-only and LLM-assisted methods in data extraction …

Assessing the ability of ChatGPT to extract natural product bioactivity and biosynthesis data from publications

TL Kalmer, CMF Ancajas, Z Cheng, AS Oyedele… - bioRxiv, 2024 - biorxiv.org
Natural products are an excellent source of therapeutics and are often discovered through
the process of genome mining, where genomes are analyzed by bioinformatic tools to …

[HTML][HTML] Evaluation of the potential value of artificial intelligence (AI) in public health using fluoride intake as the example

W Wei, T Gu, Y Cao, S Sun, D Wei, M Li, AD Fly… - Ecotoxicology and …, 2025 - Elsevier
Aim We aimed to test whether and how ChatGPT understood the epidemiological problems
related to fluoride intake and whether ChatGPT could produce novel and feasible …

COMCARE: A Collaborative Ensemble Framework for Context-Aware Medical Named Entity Recognition and Relation Extraction

M **, C Sang-Min, K Gun-Woo - Electronics, 2025 - search.proquest.com
The rapid expansion of medical information has resulted in named entity recognition (NER)
and relation extraction (RE) essential for clinical decision support systems. Medical texts …