48 citations · 66 across the 17 of their papers we have counts for
17 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…
RADAR: A Multimodal Benchmark for 3D Image-Based Radiology Report Review
Zhaoyi Sun, Minal Jagtiani, Wen-wai Yim +4
Radiology reports for the same patient examination may contain clinically meaningful discrepancies arising from interpretation differences, reporting variability, or evolving asses…
DermaVQA-DAS: Dermatology Assessment Schema (DAS) & Datasets for Closed-Ended Question Answering & Segmentation in Patient-Generated Dermatology Images
Wen-wai Yim, Yujuan Fu, Asma Ben Abacha +4
Recent advances in dermatological image analysis have been driven by large-scale annotated datasets; however, most existing benchmarks focus on dermatoscopic images and lack patien…
UW-BioNLP at ChemoTimelines 2025: Thinking, Fine-Tuning, and Dictionary-Enhanced LLM Systems for Chemotherapy Timeline Extraction
Tianmai M. Zhang, Zhaoyi Sun, Sihang Zeng +5
The ChemoTimelines shared task benchmarks methods for constructing timelines of systemic anticancer treatment from electronic health records of cancer patients. This paper describe…
A Systematic Analysis of Large Language Models with RAG-enabled Dynamic Prompting for Medical Error Detection and Correction
Farzad Ahmed, Joniel Augustine Jerome, Meliha Yetisgen +1
Objective: Clinical documentation contains factual, diagnostic, and management errors that can compromise patient safety. Large language models (LLMs) may help detect and correct s…
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.…