4 papers
Traj-Evolve: A Self-Evolving Multi-Agent System for Patient Trajectory Modeling in Lung Cancer Early Detection
Sihang Zeng, Matthew Thompson, Ruth Etzioni +1
Modeling patient trajectories from longitudinal electronic health records (EHRs) requires reasoning over sparse, noisy, and long-context multimodal sequences. Existing LLM-based mu…
Traj-CoA: Patient Trajectory Modeling via Chain-of-Agents for Lung Cancer Risk Prediction
Sihang Zeng, Yujuan Fu, Sitong Zhou +6
Large language models (LLMs) offer a generalizable approach for modeling patient trajectories, but suffer from the long and noisy nature of electronic health records (EHR) data in…
TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection
Sihang Zeng, Young Won Kim, Wilson Lau +4
Accurate estimation of cancer risk from longitudinal electronic health records (EHRs) could support earlier detection and improved care, but modeling such complex patient trajector…
TrajSurv: Learning Continuous Latent Trajectories from Electronic Health Records for Trustworthy Survival Prediction
Sihang Zeng, Lucas Jing Liu, Jun Wen +3
Trustworthy survival prediction is essential for clinical decision making. Longitudinal electronic health records (EHRs) provide a uniquely powerful opportunity for the prediction.…