Assessment; Decision support systems; Linguistic summarizing; Multidimensional data; Propositions; Spatial-temporal model; Tendency

Cardiovascular (CV) diseases represent a significant proportion of all diseases and fatal events worldwide. With the development of screening and digital technologies, as well as smart medical gadgets, the number of sources and volume of medical data characterizing CV health is increasing. It creates conditions for the development of patient support systems for the early detection and prevention of the development of CV diseases. The article presents the theoretical provisions of the data-driven approach to the automatic assessment of individual CV health status according to a variety of indicators, including the spatial-temporal assessment model and the method for obtaining it. The proposed model of patient is focused on describing the state and changes in CV health using linguistic propositions. The conducted experimental study showed the effectiveness of the proposed approach for identifying problems with CV health of patients.