5 papers
Standalone LLM and a Pre-specified Agentic Pipeline for Explaining ICU Mortality Predictions: a Feasibility Study on the eICU Demo Dataset
Di Zhu, Chen Xie, Haoyun Zhang +5
Machine-learning models can predict ICU mortality accurately, but feature-attribution methods alone rarely provide the clinical narrative needed for bedside use. Large language mod…
Evolutionary Physics-Informed Temporal Fusion for Lane-Change Intention Prediction
Jiazhao Shi, Qiyang Xie, Ziyu Wang +7
Early lane-change intention prediction is essential for autonomous driving and ADAS, but it remains challenging because lane-changing behavior depends on evolving traffic risk, sur…
RaX-Crash: A Resource Efficient and Explainable Small Model Pipeline with an Application to City Scale Injury Severity Prediction
Di Zhu, Chen Xie, Ziwei Wang +1
New York City reports over one hundred thousand motor vehicle collisions each year, creating substantial injury and public health burden. We present RaX-Crash, a resource efficient…
Governance-Ready Small Language Models for Medical Imaging: Prompting, Abstention, and PACS Integration
Yiting Wang, Ziwei Wang, Di Zhu +2
Small Language Models (SLMs) are a practical option for narrow, workflow-relevant medical imaging utilities where privacy, latency, and cost dominate. We present a governance-ready…
A Narrative Review on Large AI Models in Lung Cancer Screening, Diagnosis, and Treatment Planning
Jiachen Zhong, Yiting Wang, Di Zhu +1
Lung cancer remains one of the most prevalent and fatal diseases worldwide, demanding accurate and timely diagnosis and treatment. Recent advancements in large AI models have signi…