The advent of large volumes of data, the use of artificial intelligence methods for processing heterogeneous data, in particular medical, is becoming increasingly relevant. The article investigate the methods of Data Mining and analyzes the features and results of their application to the classification of patients' states by the results of laboratory and other medical diagnostic methods. Particular attention is paid to naive Bayesian method, cluster analysis methods, in particular DBSCAN, PCA, and k-means, based on the identification of patients' condition clusters and analysis of the correlation of distance between them and the search for the posterior maximum. The main advantages of application of the ensemble of methods for consolidation of large volumes of data, analysis of individual characteristics of the studied object and study of the process of its behavior in the space of its states are determined.