The use of virtual patients for students and for advanced training of medical doctors is a definite pedagogic innovation. The computer-based interactive multimedia simulations of scenarios for diagnosis and treatment allow for the avoidance of the risk of improper actions in regard to a real life patient, to repeat the clinical situations an unlimited number of times, and to standardize the tasks and criteria of their completion. Virtual patients represent a factual basis of problem-based learning. This review article focuses on the use of this educational technology for the development of medical decision making skills internationally, on its pedagogical effectiveness, and on the variants of the linear and branching scenarios. Meta-analyses demonstrate the pedagogical effectiveness of virtual patients and an interest of the trainees. An integration of the virtual patients into the learning contributes to clinical training gamification, which inspires the students and medical doctors to engage in interactivity and teamwork. The creation of a repository or a web-service of multimedia virtual patients in the tradition of national clinical school is of great current interest for implementation in the system of higher and continuing medical education.

Virtual patients as a format for simulation learning in continuing medical education (review article)

The IACPaaS Platform for Developing Systems Based on Ontologies: A Decade of Use

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. 

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

Knowledge base ontology for recuperative treatment

The paper describes a fragment of the knowledge base of drug therapy for ischemic heart disease, hosted on the IACPaaS platform. Generally accepted medical terminology is used in the formation of knowledge.

FORMAL REPRESENTATION OF KNOWLEDGE ABOUT MEDICAMENTAL THERAPY FOR ISCHEMIC HEART DISEASES (detail)

/pdf/software-shell-for-creating-intelligent-systems-in-practical-4lbifiyofz.pdf

Software shell for creating intelligent systems in practical and educational medicine

/pdf/ontologies-for-the-formation-of-knowledge-bases-about-3p549y7ezj.pdf

Ontologies for the formation of knowledge bases about disease treatment in medical intelligent systems

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Software shell for creating intelligent systems in practical and educational medicine

Ontologies for the formation of knowledge bases about disease treatment in medical intelligent systems