10 papers
Entry-level guide to the use of large language models for medical research
Qiao Jin, Nicholas Wan, Robert Leaman +20
Frontier large language models (LLMs), such as GPT-5, Claude 4.5, Gemini 3, Llama 4, and DeepSeek-R1, represent a transformative class of AI tools capable of revolutionizing variou…
Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorization
Gongbo Zhang, Yifan Peng, Chunhua Weng
Retrieval-Augmented Generation (RAG) improves the factual accuracy of large language model (LLM) outputs by grounding generation in external knowledge. Recent agentic RAG systems e…
CPGPrompt: Translating Clinical Guidelines into LLM-Executable Decision Support
Ruiqi Deng, Geoffrey Martin, Tony Wang +6
Clinical practice guidelines (CPGs) provide evidence-based recommendations for patient care; however, integrating them into Artificial Intelligence (AI) remains challenging. Previo…
Toward Global Large Language Models in Medicine
Rui Yang, Huitao Li, Weihao Xuan +47
Despite continuous advances in medical technology, the global distribution of health care resources remains uneven. The development of large language models (LLMs) has transformed…
EvidenceOutcomes: a Dataset of Clinical Trial Publications with Clinically Meaningful Outcomes
Yiliang Zhou, Abigail M. Newbury, Gongbo Zhang +4
The fundamental process of evidence extraction and synthesis in evidence-based medicine involves extracting PICO (Population, Intervention, Comparison, and Outcome) elements from b…
Natural Language Processing in Support of Evidence-based Medicine: A Scoping Review
Zihan Xu, Haotian Ma, Gongbo Zhang +3
Evidence-based medicine (EBM) is at the forefront of modern healthcare, emphasizing the use of the best available scientific evidence to guide clinical decisions. Due to the sheer…