3 citations · 3 across the 2 of their papers we have counts for
6 papers
DT-Transformer: A Foundation Model for Disease Trajectory Prediction on a Real-world Health System
Yunying Zhu, Andrew R Weckstein, Kueiyu Joshua Lin +1
Accurate disease trajectory prediction is critical for early intervention, resource allocation, and improving long-term outcomes. While electronic health records (EHRs) provide a r…
BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text
Jiageng Wu, Bowen Gu, Ren Zhou +14
Large language models (LLMs) hold great promise for medical applications and are evolving rapidly, with new models being released at an accelerated pace. However, benchmarking on l…
Undersmoothed LASSO Models for Propensity Score Weighting and Synthetic Negative Control Exposures for Bias Detection
Richard Wyss, Ben B. Hansen, Georg Hahn +2
The propensity score (PS) is often used to control for large numbers of covariates in high-dimensional healthcare database studies. The least absolute shrinkage and selection opera…
Why Chain of Thought Fails in Clinical Text Understanding
Jiageng Wu, Kevin Xie, Bowen Gu +3
Large language models (LLMs) are increasingly being applied to clinical care, a domain where both accuracy and transparent reasoning are critical for safe and trustworthy deploymen…
Scalable Medication Extraction and Discontinuation Identification from Electronic Health Records Using Large Language Models
Chong Shao, Douglas Snyder, Chiran Li +7
Identifying medication discontinuations in electronic health records (EHRs) is vital for patient safety but is often hindered by information being buried in unstructured notes. Thi…
Probabilistic Medical Predictions of Large Language Models
Bowen Gu, Rishi J. Desai, Kueiyu Joshua Lin +1
Large Language Models (LLMs) have shown promise in clinical applications through prompt engineering, allowing flexible clinical predictions. However, they struggle to produce relia…