4 citations · 6 across the 5 of their papers we have counts for
6 papers
Challenges of Auditing: Variability in Outputs of Large Language Models for Health
Yuan Pu, Yewon Chang, Furong Jia +4
People increasingly use frontier AI models for health advice, but via different access modes (e.g., ChatGPT, ChatGPT Health, APIs) with varying settings. Here, we find systematic d…
MedRedFlag: Investigating how LLMs Redirect Misconceptions in Real-World Health Communication
Sraavya Sambara, Yuan Pu, Ayman Ali +3
Real-world health questions from patients often unintentionally embed false assumptions or premises. In such cases, safe medical communication typically involves redirection: addre…
Counting Clues: A Lightweight Probabilistic Baseline Can Match an LLM
Furong Jia, Yuan Pu, Finn Guo +1
Large language models (LLMs) excel on multiple-choice clinical diagnosis benchmarks, yet it is unclear how much of this performance reflects underlying probabilistic reasoning. We…
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium
Amin Adibi, Xu Cao, Zongliang Ji +39
The fourth Machine Learning for Health (ML4H) symposium was held in person on December 15th and 16th, 2024, in the traditional, ancestral, and unceded territories of the Musqueam,…
Trajectory Flow Matching with Applications to Clinical Time Series Modeling
Xi Zhang, Yuan Pu, Yuki Kawamura +4
Modeling stochastic and irregularly sampled time series is a challenging problem found in a wide range of applications, especially in medicine. Neural stochastic differential equat…
Assessing the Usability of GutGPT: A Simulation Study of an AI Clinical Decision Support System for Gastrointestinal Bleeding Risk
Colleen Chan, Kisung You, Sunny Chung +10
Applications of large language models (LLMs) like ChatGPT have potential to enhance clinical decision support through conversational interfaces. However, challenges of human-algori…