ANALYSIS OF SOCIALLY SIGNIFICANT DISEASES AND DATA PROCESSING USING INTELLIGENT TECHNOLOGIES

Nowadays, data mining is the primary tool for extracting valuable information from voluminous datasets.

This process reveals hidden patterns, trends and important regularities, providing a deeper understanding of data and helping to make informed decisions. In today's information society, data mining plays an important role in medicine, biology, economics, and many other fields. Its use helps to improve the quality of life of people, optimize processes and develop effective strategies in various fields of activity.

This study is designed to analyze socially significant diseases, such as tuberculosis, in the Republic of Kazakhstan using data mining methods. A retrospective analysis of the data of the republic for the period from 2010 to 2022 was carried out, which allowed to determine the dynamics of morbidity, recovery and mortality from tuberculosis. Statistica software was used and Data Mining software technologies were applied, allowing to conduct statistical analysis, identify relationships and correlations, as well as to predict the future development of the disease.

The results obtained will help to improve the state of tuberculosis in the country and identify factors affecting the spread of the disease and develop effective strategies for preventive treatment of the population. In order to improve the effectiveness of the fight against epidemiological threats and to improve public health.