4 citations · 4 across the 6 of their papers we have counts for
7 papers
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-enabled Medical Devices
Mohammadreza Hallajiyan, Xueren Ge, Athish Pranav Dharmalingam +4
The growing integration of artificial intelligence (AI) and machine learning (ML) in medical systems requires effective measures to address emerging security risks. One such risk i…
EMSDialog: Synthetic Multi-person Emergency Medical Service Dialogue Generation from Electronic Patient Care Reports via Multi-LLM Agents
Xueren Ge, Sahil Murtaza, Anthony Cortez +1
Conversational diagnosis prediction requires models to track evolving evidence in streaming clinical conversations and decide when to commit to a diagnosis. Existing medical dialog…
Expert-Guided Prompting and Retrieval-Augmented Generation for Emergency Medical Service Question Answering
Xueren Ge, Sahil Murtaza, Anthony Cortez +1
Large language models (LLMs) have shown promise in medical question answering, yet they often overlook the domain-specific expertise that professionals depend on, such as the clini…
MMSense: Adapting Vision-based Foundation Model for Multi-task Multi-modal Wireless Sensing
Zhizhen Li, Xuanhao Luo, Xueren Ge +3
Large AI models have been widely adopted in wireless communications for channel modeling, beamforming, and resource optimization. However, most existing efforts remain limited to s…
EgoEMS: A High-Fidelity Multimodal Egocentric Dataset for Cognitive Assistance in Emergency Medical Services
Keshara Weerasinghe, Xueren Ge, Tessa Heick +5
Emergency Medical Services (EMS) are critical to patient survival in emergencies, but first responders often face intense cognitive demands in high-stakes situations. AI cognitive…
Real-Time Multimodal Cognitive Assistant for Emergency Medical Services
Keshara Weerasinghe, Saahith Janapati, Xueren Ge +4
Emergency Medical Services (EMS) responders often operate under time-sensitive conditions, facing cognitive overload and inherent risks, requiring essential skills in critical thin…
DKEC: Domain Knowledge Enhanced Multi-Label Classification for Diagnosis Prediction
Xueren Ge, Satpathy Abhishek, Ronald Dean Williams +2
Multi-label text classification (MLTC) tasks in the medical domain often face the long-tail label distribution problem. Prior works have explored hierarchical label structures to f…