Russian version English version
Volume 11   Issue 1   Year 2016
Guliev R.R., Senko O.V., Zateyshchikov D.A., Nosikov V.V., Uporov I.V., Kuznetsova A.V., Evdokimova M.A., Tereshchenko S.N., Akatova E.V., Glaser M.G., Galyavich A.S., Koziolova N.A., Yagoda A.V., Boeva O.I., Shlyk S.V., Levashov S.Y., Konstantinov V.O., Brazhnik V.A.,Varfolomeev S.D., Kurochkin I.N.

The use of optimal partitionings for multiparameter data analysis in clinical trials

Mathematical Biology & Bioinformatics. 2016;11(1):46-63.

doi: 10.17537/2016.11.46.



  1. World Health Organization. The top 10 causes of death. (accessed 03 February 2016).
  2. Antman E.M., Cohen M., Bernink P.J., McCabe C.H., Horacek T., Papuchis G., Mautner B., Corbalan R., Radley D., Braunwald E. The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. Journal of the American Medical Association. 2000;284(7):835-842. doi: 10.1001/jama.284.7.835
  3. Pollack C.V. Jr., Sites F.D., Shofer F.S., Sease K.L., Hollander J.E. Application of the TIMI Risk Score for Unstable Angina and Non-ST Elevation Acute Coronary Syndrome to an Unselected Emergency Department Chest Pain Population. Academic Emergency Medicine. 2006;13(1):13-18. doi: 10.1111/j.1553-2712.2006.tb00978.x
  4. Boersma E., Pieper K.S., Steyerberg E.W., Wilcox R.G., Chang W., Lee K.L., Akkerhuis K.M., Harrington R.A., Deckers J.W., Armstrong P.W. et al. Predictors of outcome in patients with acute coronary syndromes without persistent ST-segment elevation. Results from an international trial of 9461 patients. Circulation. 2000;101(22):2557-2567. doi: 10.1161/01.CIR.101.22.2557
  5. Granger C.B., Goldberg R.J., Dabbous O., Pieper K.S., Eagle K.A., Cannon C.P., Van de Werf F., Avezum A., Goodman S.G., Flather M.D. et al. Predictors of hospital mortality in the global registry of acute coronary events. Archives of Internal Medicine. 2003;163(19):2345-2353. doi: 10.1001/archinte.163.19.2345
  6. Eagle K.A., Lim M.J., Dabbous O.H., Pieper K.S., Goldberg R.J., Van de Werf F., Goodman S.G., Granger C.B., Steg P.G., Gore J.M. et al. A validated prediction model for all forms of acute coronary syndrome. Estimating the risk of 6-month postdischarge death in an international registry. Journal of the American Medical Association. 2004;291(22):2727-2733. doi: 10.1001/jama.291.22.2727
  7. Senko O.V., Kuznetsova A.V. A recognition method based on collective decision making using systems of regularities of various types. Pattern Recognition and Image Analysis. 2010;20(2):152-162. doi: 10.1134/S1054661810020069
  8. Kuznetsova A.V., Kostomarova I.V., Senko O.V. Modification of the method of optimal valid partitioning for comparison of patterns related to the occurrence of ischemic stroke in two groups of patients. Pattern Recognition and Image Analysis. 2014;24(1):114-123. doi: 10.1134/S105466181401009X
  9. Senko O.V., Kuznetsova A.V. The Optimal Valid Partitioning Procedures. InterStat. 2006;2.
  10. Kuznetsov V.A., Senko O.V., Kuznetsova A.V., Semenova L.P., Aleshchenko A.V., Gladysheva T.B., Ivshina A.V. Recognition of fuzzy-system using the statistically weighted syndromes technique and its application for the immunohematol characteristics of norm and chromic pathology. Khimiceskaya fizika (Russian Journal of Physical Chemistry B). 1996;15(1):81-100 (in Russ.).
  11. Ivshina A.V., George J., Senko O.V., Mow B., Putti T.C., Smeds J., Lindahl T., Pawitan Y., Hall P., Nordgren H., Wong J.E.L., Liu E.T., Bergh J., Kuznetsov V.A., Miller L.D. Genetic Reclassification of Histologic Grade Delineates New Clinical Subtypes of Breast Cancer. Cancer Research. 2006;66(21):10292-10301. doi: 10.1158/0008-5472.CAN-05-4414
  12. Zakovriashin A.S., Dorovskikh I.V., Zakovriashina S.E., Sen'ko O.V., Kuznetsova A.V., Kozlov A.A. Prognosis of remote consequences of combat mental trauma using logical statistical methods. Zhurnal Nevrologii i Psikhiatrii S.S. Korsakova (Journal of Neurology and Psychiatry). 2006;106(3):31-38 (in Russ.).
  13. Hastie T., Tibshirani R., Friedman J. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer; 2009. 533 p. doi: 10.1007/978-0-387-84858-7
  14. Zateischikov D.A., Volkova E.G., Guz I.O., Evdokimova M.A., Aseicheva O.Yu., Galyavich A.S., Tereschenko S.N., Kaziolova N.A., Glezer M.G., Jagoda A.V. et al. Treatment of patients underwent acute coronary syndrome according to the data of Russian multicentral prospective observational study. Pharmateka. 2009(12):109-113 (in Russ.).
  15. Chumakova O.S., Selezneva N.D., Evdokimova M.A., Osmolovskaya V.S., Kochkina M.S., Aseycheva O.Yu., Minushkina L.O., Baklanova T.N., Talysin P.A., Tereshchenko S.N. et al. Prognostic value of aortic stenosis in patients after exacerbation of ischemic heart disease. Cardiology. 2011(1):23-28 (in Russ.).
  16. Blagodatskikh K.A., Evdokimova M.A., Agapkina Yu.V., Nikitin A.G., Brovkin A.N., Pushkov A.A., Blagodatskikh E.G., Kudryashova O.Yu., Osmolovskaya V.S., Minushkina L.O. et al. The polymorphisms G(−174)C in IL6 gene and G(−1082)A in IL10 gene are associated with poor outcomes in patients with acute coronary syndrome. Journal of Molecular Biology. 2010;44(5):741-747. doi: 10.1134/S0026893310050092
  17. Blagodatskikh K.A., Nikitin A.G., Pushkov A.A., Blagodatskikh E.G., Osmolovskaya V.S., Aseicheva O.Yu., Baklanova T.N., Talyzin P.A., Tereshchenko S.N., Dzhaiani N.A. et al. Polymorphic markers G2667C, G3014A, C3872T, A5237G of CRP gene and genetic association with unfavourable outcomes of coronary artery disease in patients with history of acute ischemic heart disease. Journal of Medical Genetics. 2011;10(4):3-9 (in Russ.).
  18. BMI Classification. World Health Organization: Global Database on Body Mass Index. (accessed 03 February 2016).
  19. Cockroft D.W., Gault M.H. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16(1):31-41. doi: 10.1159/000180580
  20. Wing R.R., Matthews K.A., Kuller L.H., Meilahn E.N., Plantinga P. Waist to hip ratio in middle-aged women. Associations with behavioral and psychosocial factors and with changes in cardiovascular risk factors. Arteriosclerosis, Thrombosis, and Vascular Biology. 1991;11(5):1250-1257. doi: 10.1161/01.ATV.11.5.1250
  21. Kuznetsova A.V., Kostomarova I.V., Senko O.V. Logical and statistical analysis of relationship between clinical and laboratory indices and disturbances of cerebral blood circulation in elderly patients with chronic ischemia of the brain. Mathematical Biology and Bioinformatics. 2013;8(1):182-224 (in Russ.). doi: 10.17537/2013.8.182
  22. Kuznetsova A.V., Kostomarova I.V., Vodolagina N.N., Malygina N.F., Senko O.V. Study of effects of clinical and genetic factors on severity of discirculatory encephalopathy with the help of pattern recognition methods. Mathematical Biology and Bioinformatics. 2011;6(1):115-146 (in Russ.). doi: 10.17537/2011.6.115
  23. Paklin N. Logisticheskaia regressiia i ROC-analiz - matematicheskii apparat (Logistic Regression and ROC-analysis - mathematical instrument). BaseGroup Labs: Data analysis technologies. (accessed 03 February 2016) (in Russ.).
  24. Vorontsov K.V. A combinatorial approach to assessing the quality of training algorithms. Matematicheskie voprosy kibernetiki (Mathematical Problems of Cybernetics). 2004;13:5-36 (in Russ.).
  25. IBM SPSS Statistics 23 Documentation. (accessed 03 February 2016).
  26. IBM SPSS Modeler 17.0 Documentation. (accessed 03 February 2016).
  27. IBM SPSS Modeler 17 Modeling Nodes. (accessed 03 February 2016).
  28. GRACE 2.0 ACS Risk Calculator. (accessed 03 February 2016).
Table of Contents Original Article
Math. Biol. Bioinf.
doi: 10.17537/2016.11.46
published in Russian

Abstract (rus.)
Abstract (eng.)
Full text (rus., pdf)


  Copyright IMPB RAS © 2005-2024