Publications

Below is a growing list of our publications exploring how large language models can support emergency department teams.

• Fine-tuned large language models guided by physician feedback can improve patient chart summarization for emergency departments
  ICEM 2025 – International Conference on Emergency Medicine – Conference Presentation
  Authors: Jiajun Wu, Hanzhe Wei, Braden Teitge, Jessalyn Holodinsky, Kyle Exner, Steve Drew
  Demonstrates how clinician-in-the-loop fine-tuning boosts the quality and utility of ED chart summaries.

• Small Language Models for Emergency Departments Decision Support: A Benchmark Study
  Accepted to 2025 IEEE International Conference on Autonomous and Trusted Computing (ATC 2025) – Conference Paper
  Authors: Zirui Wang, Jiajun Wu, Braden Teitge, Jessalyn Holodinsky, Steve Drew
  Evaluates compact models for ED decision-support tasks, highlighting trade-offs between accuracy, latency, and deployability.

• Dual-stage and Lightweight Patient Chart Summarization for Emergency Physicians
  Accepted at IEEE Annual Congress on Artificial Intelligence of Things (IEEE AIoT) 2025 – Conference Paper
  Authors: Jiajun Wu, Swaleh Zaidi, Braden Teitge, Henry Leung, Jiayu Zhou, Jessalyn Holodinsky, Steve Drew
  Introduces a two-step summarization pipeline that balances comprehension with speed for frontline clinicians.