5 papers
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
Yue Huang, Chujie Gao, Siyuan Wu +63
Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions.…
Personalizing Prostate Cancer Education for Patients Using an EHR-Integrated LLM Agent
Yuexing Hao, Jason Holmes, Mark R. Waddle +10
Cancer patients often lack timely education and personalized support due to clinician workload. This quality improvement study develops and evaluates a Large Language Model (LLM) a…
Towards Better Health Conversations: The Benefits of Context-seeking
Rory Sayres, Yuexing Hao, Abbi Ward +21
Navigating health questions can be daunting in the modern information landscape. Large language models (LLMs) may provide tailored, accessible information, but also risk being inac…
The MedPerturb Dataset: What Non-Content Perturbations Reveal About Human and Clinical LLM Decision Making
Abinitha Gourabathina, Yuexing Hao, Walter Gerych +1
Clinical robustness is critical to the safe deployment of medical Large Language Models (LLMs), but key questions remain about how LLMs and humans may differ in response to the rea…
MedPAIR: Measuring Physicians and AI Relevance Alignment in Medical Question Answering
Yuexing Hao, Kumail Alhamoud, Hyewon Jeong +6
Large Language Models (LLMs) have demonstrated remarkable performance on various medical question-answering (QA) benchmarks, including standardized medical exams. However, correct…