Knowledge Graph Formation Using LLM for Disease Treatment in Decision Support Systems

The article presents an advanced method for creating knowledge graphs, applicable in medical decision support systems. It focuses on adapting the method to various clinical guidelines, making it particularly valuable in the medi¬cal field. The developed universal ontological pattern allows for the formation of knowledge bases for a wide range of diseases, making the process flexible and scalable without the need for specific programming. This approach significantly reduces the labor intensity of creating medical support systems and facilitates their integration and adaptation to various clinical conditions and requirements. The practical significance of the method was confirmed in the management systems for the therapy of various diseases, including allergic rhinitis, underscoring its universality and applicability in the current medical context. The effectiveness of the proposed approach opens new perspectives for the development and improvement of medical information systems, contributing to the improvement of patient care and treatment quality. Thus, the article makes a significant contribution to the advancement of information technology in medicine, offering a solution that can be adapted for a wide range of medical applications and research.