activity
20232026
most citedEnvironment Scan of Generative AI Infrastructure for Clinical and Translational Science

10 citations · 18 across the 14 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2026★ 1 cited

Toward Global Large Language Models in Medicine

Rui Yang, Huitao Li, Weihao Xuan +48

Despite continuous advances in medical technology, the global distribution of health care resources remains uneven. The development of large language models (LLMs) has transformed…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

Semi-Supervised Learning from Small Annotated Data and Large Unlabeled Data for Fine-grained PICO Entity Recognition

Fangyi Chen, Gongbo Zhang, Yilu Fang +2

Objective: Extracting PICO elements -- Participants, Intervention, Comparison, and Outcomes -- from clinical trial literature is essential for clinical evidence retrieval, appraisa…

cs.CL2024

A MapReduce Approach to Effectively Utilize Long Context Information in Retrieval Augmented Language Models

Gongbo Zhang, Zihan Xu, Qiao Jin +8

While holding great promise for improving and facilitating healthcare, large language models (LLMs) struggle to produce up-to-date responses on evolving topics due to outdated know…

cs.CL2024★ 2 cited

Closing the gap between open-source and commercial large language models for medical evidence summarization

Gongbo Zhang, Qiao Jin, Yiliang Zhou +11

Large language models (LLMs) hold great promise in summarizing medical evidence. Most recent studies focus on the application of proprietary LLMs. Using proprietary LLMs introduces…