REMEDIUMREMEDIUM1561-59362658-3534Joint-Stock Company Chicot127810.21518/1561-5936-2018-7-8-30-40Original ArticleMedical information system's Big Data Analytics based on Cluster analysis: patients with Diabetes Mellitus type 1MinushkinaL. O.noemail@neicon.ruKolesnichenkoO. YU.noemail@neicon.ruMazelisA. L.noemail@neicon.ruSoldatovD. A.noemail@neicon.ruKolesnichenkoYU. YU.noemail@neicon.ruMartynovA. V.noemail@neicon.ruPulitV. V.noemail@neicon.ruDolzhenkovA. N.noemail@neicon.ruGrigorevskyI. N.noemail@neicon.ruMazelisL. S.noemail@neicon.ruCentral State Medical Academy at the Department of Presidential AffairsInstitute of sociology, psychology and humanitiesI.M. Sechenov First Moscow State Medical UniversityVladivostok State University of Economics and Service4UzgraphSP.ARMAylamazyan Program Systems Institute of Russian Academy of SciencesNational Supercomputing Technology Platform071220187-8304018032022Copyright © 2018,2018Cluster analysis of medical information system’s records used to find direct and indirect indications to differences in the hospital management of patients with Diabetes Mellitus type 1, according to the prescribed diagnostic examinations and surgery. This approach allows to investigate disease’s pathogenetic mechanisms and provides predictive analytics of patients flow for more personalized treatment. Five clusters have been identified. Open international genetic databases were analyzed additionally in terms of some key pathogenesis molecular complexes. 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