This research demonstrates how large language models can identify reports of gastrointestinal illness in restaurant reviews, creating a novel public health monitoring system.

• Developed an innovative annotation schema for GI illness detection in consumer reviews
• Created a specialized LLM system to extract illness reports from unstructured text
• Established a new approach for disease surveillance that doesn't rely on healthcare system interactions
• Provides health officials with earlier detection capabilities for potential outbreaks

This research matters for public health security by extending traditional surveillance methods to capture illness cases that typically go unreported, potentially accelerating outbreak response and improving food safety oversight.

Review GIDE -- Restaurant Review Gastrointestinal Illness Detection and Extraction with Large Language Models