Knowledge Graph

Clinical natural language processing requires methods that can address domainspecific challenges, such as complex medical terminology and clinical contexts. Recently, large language models (LLMs) have shown promise in this domain. Yet, their direct deployment can lead to privacy issues and are constrained by resources.

Healthcare knowledge graphs (HKGs) are valuable tools for organizing biomedical concepts and their relationships with interpretable structures. The recent advent of large language models (LLMs) has paved the way for building more comprehensive and accurate HKGs.