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Current challenges facing the theory and practice in aging sciences require the use and develop ment of new methods of investigation of observational and experimental data. This is associated with both the extensive development of the measuring and experimental basis of biological research and the progress in information support of studies in aging. As a result, large databases containing information on the state of health of vast groups of people who survived to anadvanced age have been created. The combination of achievements in these directions make it possible to apply data mining methods that are successfully used for solving intricate tasks in economics, medical diagnostics,organization of the Internet, and other fields of sci ence and technology for solving tasks in gerontology and geriatrics. This review provides some examples of the use of data mining methods in gerontology.