collaborators

10 papers

cs.AI2026

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…

cs.AI2026

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…

cs.CL2026

RadTimeline: Timeline Summarization for Longitudinal Radiological Lung Findings

Sitong Zhou, Meliha Yetisgen, Mari Ostendorf

Tracking findings in longitudinal radiology reports is crucial for accurately identifying disease progression, and the time-consuming process would benefit from automatic summariza…

cs.CV2026

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…

cs.CV2025

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…

cs.CL2025

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…