1 citations · 1 across the 7 of their papers we have counts for
9 papers
A Source-Grounded Framework for Constructing and Evaluating Progressive Multimodal Diagnostic Dialogues from Clinical Case Reports
Yufan Wang, Rui Yang, Yi Liu +2
Clinical diagnosis requires progressive integration of patient history, physical examination, laboratory findings, medical images, and diagnostic-informative tests. However, most m…
Evaluating Multi-Turn Multimodal Diagnostic Reasoning on Challenging Real-World Clinical Cases
Rui Yang, Weihao Xuan, Yi Lin +23
Clinical diagnostic evaluation should not only assess whether models can provide correct diagnoses, but also reflect the realities of clinical practice, including progressive discl…
Fracture Risk Prediction in Adults Over 50 Years Old Using DXA and EHR: Comparison of Traditional and Machine Learning Models in Two Large Cohorts
Jiahe Qian, Hao Dai, Kunyu Yu +6
Accurate fracture risk prediction is important for osteoporosis management, but commonly used clinical tools may not fully use information available in electronic health records (E…
Towards end-to-end LLM-based censoring-aware survival analysis
Yishu Wei, Hexin Dong, Yi Lin +3
Objective: Survival analysis is central to medical prediction, yet large language models (LLMs) are rarely used as end-to-end survival models because censoring prevents straightfor…
Comparing LLM and Fine-Tuned Model Performance on NVDRS Circumstance Extraction with Varying Prompt Complexity
Geoffrey Martin, Xuan Zhong Feng, Yifan Peng
Suicide is a leading cause of death in the United States, and understanding the circumstances that precede it requires extracting structured information from death investigation na…
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…
Curation and Extraction of Drug-Related Entities from Reddit Platform
Zewei Wang, Zihan Xu, Yishu Wei +2
Physicians learn primarily about illicit drugs from clinical overdose cases, limiting their understanding of real-world usage. Meanwhile, drug users share first-hand experiences on…
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…
Gender Bias in Large Language Models for Healthcare: Assignment Consistency and Clinical Implications
Mingxuan Liu, Yuhe Ke, Wentao Zhu +9
The integration of large language models (LLMs) into healthcare holds promise to enhance clinical decision-making, yet their susceptibility to biases remains a critical concern. Ge…