2 citations · 3 across the 10 of their papers we have counts for
11 papers
What Makes a Medical Checker Trainable? Diagnosing Signal Collapse and Reward Hacking in Checker-Guided RAG for Biomedical QA
Yuelyu Ji, Min Gu Kwak, Hang Zhang +3
Medical RAG needs evidence-grounded claims, so plugging a claim-level NLI checker into retrieval-augmented RL is intuitive. \textbf{We find that the checker's \emph{output distribu…
A Scoping Review of LLM-as-a-Judge in Healthcare and the MedJUDGE Framework
Chenyu Li, Zohaib Akhtar, Mingu Kwak +13
As large language models (LLMs) increasingly generate and process clinical text, scalable evaluation has become critical. LLM-as-a-Judge (LaaJ), which uses LLMs to evaluate model o…
Scaling Medical Reasoning Verification via Tool-Integrated Reinforcement Learning
Hang Zhang, Ruheng Wang, Yuelyu Ji +7
Large language models have achieved strong performance on medical reasoning benchmarks, yet their deployment in clinical settings demands rigorous verification to ensure factual ac…
MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation
Yuelyu Ji, Min Gu Kwak, Hang Zhang +3
Biomedical retrieval-augmented generation (RAG) can ground LLM answers in medical literature, yet long-form outputs often contain isolated unsupported or contradictory claims with…
Orchestrator Multi-Agent Clinical Decision Support System for Secondary Headache Diagnosis in Primary Care
Xizhi Wu, Nelly Estefanie Garduno-Rapp, Justin F Rousseau +6
Unlike most primary headaches, secondary headaches need specialized care and can have devastating consequences if not treated promptly. Clinical guidelines highlight several 'red f…
Automated Extraction of Fluoropyrimidine Treatment and Treatment-Related Toxicities from Clinical Notes Using Natural Language Processing
Xizhi Wu, Madeline S. Kreider, Philip E. Empey +2
Objective: Fluoropyrimidines are widely prescribed for colorectal and breast cancers, but are associated with toxicities such as hand-foot syndrome and cardiotoxicity. Since toxici…
Generative Foundation Model for Structured and Unstructured Electronic Health Records
Sonish Sivarajkumar, Hang Zhang, Yuelyu Ji +6
Electronic health records (EHRs) are rich clinical data sources but complex repositories of patient data, spanning structured elements (demographics, vitals, lab results, codes), u…
Mitigating the Risk of Health Inequity Exacerbated by Large Language Models
Yuelyu Ji, Wenhe Ma, Sonish Sivarajkumar +6
Recent advancements in large language models have demonstrated their potential in numerous medical applications, particularly in automating clinical trial matching for translationa…
SDoH-GPT: Using Large Language Models to Extract Social Determinants of Health (SDoH)
Bernardo Consoli, Xizhi Wu, Song Wang +10
Extracting social determinants of health (SDoH) from unstructured medical notes depends heavily on labor-intensive annotations, which are typically task-specific, hampering reusabi…
A Framework for Human Evaluation of Large Language Models in Healthcare Derived from Literature Review
Thomas Yu Chow Tam, Sonish Sivarajkumar, Sumit Kapoor +12
With generative artificial intelligence (AI), particularly large language models (LLMs), continuing to make inroads in healthcare, it is critical to supplement traditional automate…
Enhancing Large Language Models for Clinical Decision Support by Incorporating Clinical Practice Guidelines
David Oniani, Xizhi Wu, Shyam Visweswaran +4
Background Large Language Models (LLMs), enhanced with Clinical Practice Guidelines (CPGs), can significantly improve Clinical Decision Support (CDS). However, methods for incorpor…