8 citations · 46 across the 26 of their papers we have counts for
14 papers · 1 filter
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…
An Agentic AI System for Multi-Framework Communication Coding
Bohao Yang, Rui Yang, Joshua M. Biro +15
Clinical communication is central to patient outcomes, yet large-scale human annotation of patient-provider conversation remains labor-intensive, inconsistent, and difficult to sca…
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…
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…
TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots
Tianyu Liu, Weihao Xuan, Hao Wu +15
Advances in AI have introduced several strong models in computational pathology to usher it into the era of multi-modal diagnosis, analysis, and interpretation. However, the curren…
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…
Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards
Fang Wu, Aaron Tu, Weihao Xuan +21
Reinforcement learning with verifiable rewards (RLVR) is a practical, scalable way to improve large language models on math, code, and other structured tasks. However, we argue tha…
The Evolving Landscape of Generative Large Language Models and Traditional Natural Language Processing in Medicine
Rui Yang, Huitao Li, Matthew Yu Heng Wong +12
Natural language processing (NLP) has been traditionally applied to medicine, and generative large language models (LLMs) have become prominent recently. However, the differences b…
Retrieval-Augmented Generation in Biomedicine: A Survey of Technologies, Datasets, and Clinical Applications
Jiawei He, Boya Zhang, Hossein Rouhizadeh +6
Large language models (LLMs) in biomedicine face a fundamental conflict between static parameter knowledge and the dynamic nature of clinical evidence. Retrieval-Augmented Generati…
HealthGenie: Empowering Users with Healthy Dietary Guidance through Knowledge Graph and Large Language Models
Fan Gao, Xinjie Zhao, Ding Xia +6
Seeking dietary guidance often requires navigating complex professional knowledge while accommodating individual health conditions. Knowledge Graphs (KGs) offer structured and inte…
Enabling Inclusive Systematic Reviews: Incorporating Preprint Articles with Large Language Model-Driven Evaluations
Rui Yang, Jiayi Tong, Haoyuan Wang +8
Background. Systematic reviews in comparative effectiveness research require timely evidence synthesis. Preprints accelerate knowledge dissemination but vary in quality, posing cha…
MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation
Weihao Xuan, Rui Yang, Heli Qi +29
Existing large language model (LLM) evaluation benchmarks primarily focus on English, while current multilingual tasks lack parallel questions that specifically assess cross-lingui…
ReAgent: Reversible Multi-Agent Reasoning for Knowledge-Enhanced Multi-Hop QA
Xinjie Zhao, Fan Gao, Xingyu Song +7
Recent advances in large language models (LLMs) have significantly improved multi-hop question answering (QA) through direct Chain-of-Thought (CoT) reasoning. However, the irrevers…
GraphCheck: Breaking Long-Term Text Barriers with Extracted Knowledge Graph-Powered Fact-Checking
Yingjian Chen, Haoran Liu, Yinhong Liu +8
Large language models (LLMs) are widely used, but they often generate subtle factual errors, especially in long-form text. These errors are fatal in some specialized domains such a…