Large Language Models for Biomedical Knowledge Graph Construction: Information extraction from EMR notes

Understand

The automatic construction of knowledge graphs (KGs) is an important research area in medicine, with far-reaching applications spanning drug discovery and clinical trial design.

• These applications hinge on the accurate identification of interactions among medical and biological entities.
• In this study, we propose an end-to-end machine learning solution based on large language models (LLMs) that utilize electronic medical record notes to construct KGs.
• The entities used in the KG construction process are diseases, factors, treatments, as well as manifestations that coexist with the patient while experiencing the disease.