This research leverages Large Language Models (LLMs) to classify unstructured patient comments for improved healthcare quality assessment.

• Addresses the challenge of analyzing free-text patient feedback without extensive labeled data
• Implements a PHI detection system to maintain patient privacy and data security
• Demonstrates how LLMs can extract meaningful insights from patient comments for hospital quality improvement
• Creates a framework that bridges the gap between raw patient feedback and actionable healthcare insights

This innovation is transforming medical quality management by allowing hospitals to systematically understand patient experiences, identify service gaps, and drive targeted improvements in care delivery.

Large Language Models for Patient Comments Multi-Label Classification