2 citations · 6 across the 11 of their papers we have counts for
4 papers · 1 filter
KMGen: A Skill-based Approach for Synthetic Individual Patient Data Generation
Jalen Jiang, Chufan Gao, Ethan Rasmussen +2
Individual patient data (IPD) from clinical trials is the substrate for survival modeling, meta-analysis, and safety research, yet IPD is rarely released. Prior work has addressed…
Accelerating Reproducible Research in Synthetic EHR Generation
Jalen Jiang, Chufan Gao, Ethan Rasmussen +2
The generation of high-fidelity synthetic Electronic Health Records (EHR) is crucial for advancing medical research while preserving patient privacy. However, head-to-head comparis…
Utilizing Training Data to Improve LLM Reasoning for Tabular Understanding
Chufan Gao, Jintai Chen, Jimeng Sun
Automated tabular understanding and reasoning are essential tasks for data scientists. Recently, Large language models (LLMs) have become increasingly prevalent in tabular reasonin…
TrialSynth: Generation of Synthetic Sequential Clinical Trial Data
Chufan Gao, Mandis Beigi, Afrah Shafquat +2
Analyzing data from past clinical trials is part of the ongoing effort to optimize the design, implementation, and execution of new clinical trials and more efficiently bring life-…