DIGITAL TRANSFORMATION OF CONTROL RISK MANAGEMENT PROCESSES IN THE MAGNETIC RESONANCE DIAGNOSTICS SYSTEM

Authors: Tankibayeva A., Kumargazhanova S., Azamatov B., Azamatova Zh.
IRSTI 20.53.19

Abstract. The article sets the main goal of improving the quality of medical care for the population with diseases of the musculoskeletal system, using the example of MRI diagnostics of the knee joint. MRI technology is systematically considered in the article as an integrated cyberspace of augmented reality containing physically measurable indicators and calculated virtual risk parameters. The medical care system in the research tasks is represented by a composition of a vertical integration vector and a horizontal vector. The vertical integration vector is a systemic hierarchical inter-level structure, an organizational and technical link with the lower operational and technological level. The organizational and technical criterion for the systemic quality of the vertical vector is proposed to use the level of digital maturity, which is a fuzzy composition of weighted support agents: technical support; information analytical support; mathematical support; metrological support; personnel support; software. For a quantitative assessment of the level of digital maturity, a model and an algorithm based on fuzzy principles have been developed. The horizontal operational and technological vector aggregates the procedures of mandatory clinical and laboratory examination and additional ones based on radiography and ultrasound diagnostics. The working technology at the lower system level is MRI diagnostics. At this level, the main scientific and practical attention is focused on the formalization of the processes of quantitative assessment of operational risks of control and making diagnostic decisions under conditions of parametric uncertainty of control agents. For this purpose, probabilistic, simulation, statistical models and expert approaches have been developed. The adequacy of theoretical hypotheses to practical results is assessed by computer modeling, for which software applications in the Python language have been developed.

Keywords: MRI technology, system, digital maturity, fuzziness, modeling, control risks.