A knowledge base generation for creation a medical decision support system for managing the treatment process

Abstract

The strategy of scientific and technological development of the Russian Federation prioritizes the formation of new approaches to the treatment of tuberculosis, including forms with multidrug resistance. In modern conditions the fulfillment of this task is impossible without the intensive introduction of advanced digital and intelligent technologies, robotic systems and systems using artificial intelligence methods. This approach should start with an important component –the creation of a knowledge base.Aim: To create a knowledge base of drug therapy based on the appropriate ontology, to assemble a prototype of a medical decision support system for managing the treatment of patients with pulmonary tuberculosis.Material and Methods. Current scientific data and recommendations for the treatment of pulmonary tuberculosis in adults were used, according to clinical recommendations approved by the Ministry of Health of the Russian Federation in 2022. The IACPaaS platform is used to implement the intelligent service.Results. A knowledge base has been created to manage the treatment of patients with pulmonary tuberculosis, which allows you to structure knowledge about drug therapy of tuberculosis, define concepts, relationships and axioms describing this process. Each element of the ontology includes a complexly structured block of conditions that allows you to describe in a formal presentation the necessary clinical criteria that determine the conditions for creating an intelligent assistant to a phthisiologist.Conclusion. The generation of the knowledge base will make it possible to switch to personalized medicine through the rational use of anti-tuberculosis drugs, which will reduce the time and improve the effectiveness of tuberculosis treatment.