Shubham Agarwal

Improving Extraction of Clinical Event Contextual Properties from Electronic Health Records: A Comparative Study

2024 · arXiv (Cornell University)

Electronic Health Records are large repositories of valuable clinical data, with a significant portion stored in unstructured text format. This textual data includes clinical events (e.g., disorders, symptoms, findings, medications and procedures) in context that …

LongLaMP: A Benchmark for Personalized Long-form Text Generation

2024 · arXiv (Cornell University)

Long-text generation is seemingly ubiquitous in real-world applications of large language models such as generating an email or writing a review. Despite the fundamental importance and prevalence of long-text generation in many practical applications, existing …

CogStack-KCL-UCL at ArchEHR-QA 2025: Investigating Hybrid LLM Approaches for Grounded Clinical Question Answering

2025

We present our system for the ArchEHR shared task, which focuses on answering clinical and patient-facing questions grounded in real-world EHR data.Our core contribution is a 2-Stage prompting pipeline that separates evidence selection from answer …