Identifying and Characterizing Gallstone Disease from Clinical Narratives with Zero-shot Learning and Automated Prompt Optimization

Abstract We built and evaluated a zero-shot LLM pipeline with automated, task-aware prompt optimization to extract radiology and symptom fields for gallstone phenotyping from de-identified EHR text. Across symptomatic, asymptomatic, and control cohorts, it performed reliably on high-signal binary fields and symptom flags but lagged on fine-grained stone burden and complications, establishing a practical baseline and motivating targeted refinements