5 papers
ATHENA: Knowledge-guided agentic neural architecture search for AutoFormer-based electronic health record modeling
Deyi Li, Qi Xu, Lingyao Li +3
Transformer-based models are widely used for clinical prediction from electronic health records (EHRs), yet their architectures still require substantial manual tuning, and the opt…
Teaching agentic AI to learn expert reasoning for rare disease diagnosis
Minh-Ha Nguyen, Erica Gray, Bryce A. Schuler +17
Rare disease diagnosis depends on expert reasoning that is scarce and difficult to transfer; off-the-shelf large language models (LLMs) rank the correct disease first in only 35.4%…
DT-BEHRT: Disease Trajectory-aware Transformer for Interpretable Patient Representation Learning
Deyi Li, Zijun Yao, Qi Xu +4
The growing adoption of electronic health record (EHR) systems has provided unprecedented opportunities for predictive modeling to guide clinical decision making. Structured EHRs c…
From Promising Capability to Pervasive Bias: Assessing Large Language Models for Emergency Department Triage
Joseph Lee, Tianqi Shang, Jae Young Baik +4
Large Language Models (LLMs) have shown promise in clinical decision support, yet their application to triage remains underexplored. We systematically investigate the capabilities…
DynamiCare: A Dynamic Multi-Agent Framework for Interactive and Open-Ended Medical Decision-Making
Tianqi Shang, Weiqing He, Charles Zheng +3
The rise of Large Language Models (LLMs) has enabled the development of specialized AI agents with domain-specific reasoning and interaction capabilities, particularly in healthcar…