Abstract
Methods for the analysis of medical data and the results of their application to the treatment of a number of socially important diseases in important medical areas (cardiology, neurology, surgery, and oncology) are considered. The precedent approach is investigated. Practical methods of discrete analysis of training data, logical and statistical methods for searching logical regularities in data, combinatorial logic and logical statistical classification methods, and methods for estimating models and searching for "nonstandard" descriptions are presented. The results of experiments on real data are demonstrated.
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