most citedHealthGenie: Empowering Users with Healthy Dietary Guidance through Knowledge Graph and Large Language Models

1 citations · 3 across the 6 of their papers we have counts for

collaborators

13 papers

cs.CL20261 cited

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…

cs.CL20251 cited

Leveraging LLMs for Title and Abstract Screening for Systematic Review: A Cost-Effective Dynamic Few-Shot Learning Approach

Yun-Chung Liu, Rui Yang, Jonathan Chong Kai Liew +4

Systematic reviews are a key component of evidence-based medicine, playing a critical role in synthesizing existing research evidence and guiding clinical decisions. However, with…

cs.CL2025

An Agentic AI System for Multi-Framework Communication Coding

Bohao Yang, Rui Yang, Joshua M. Biro +14

Clinical communication is central to patient outcomes, yet large-scale human annotation of patient-provider conversation remains labor-intensive, inconsistent, and difficult to sca…

cs.CL2025

HealthContradict: Evaluating Biomedical Knowledge Conflicts in Language Models

Boya Zhang, Alban Bornet, Rui Yang +2

How do language models use contextual information to answer health questions? How are their responses impacted by conflicting contexts? We assess the ability of language models to…

cs.CL2025

Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations

Rui Yang, Matthew Yu Heng Wong, Huitao Li +13

The rapid growth of medical knowledge and increasing complexity of clinical practice pose challenges. In this context, large language models (LLMs) have demonstrated value; however…

q-bio.QM2025

Beyond the Clinic: A Large-Scale Evaluation of Augmenting EHR with Wearable Data for Diverse Health Prediction

Will Ke Wang, Rui Yang, Chao Pang +7

Electronic health records (EHRs) provide a powerful basis for predicting the onset of health outcomes. Yet EHRs primarily capture in-clinic events and miss aspects of daily behavio…