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Matematicheskaya Biologiya i Bioinformatika, 2016, Volume 11, Issue 1, Pages 46–63
DOI: https://doi.org/10.17537/2016.11.46 (Mi mbb250) 		 
This article is cited in 8 scientific papers (total in 8 papers)

Information and Computer Technologies in Biology and Medicine

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

R. R. Gulieva, O. V. Senkob, D. A. Zateishchikovcd, V. V. Nosikova, I. V. Uporove, A. V. Kuznetsovaa, M. A. Evdokimovacd, S. N. Tereshchenkof, E. V. Akatovag, M. G. Glaserh, A. S. Galyavichi, N. A. Koziolovaj, A. V. Yagodak, O. I. Boevak, S. V. Shlykl, S. Yu. Levashovm, V. O. Konstantinovn, V. A. Brazhnikcd, S. D. Varfolomeeva, I. N. Kurochkinea

a Emanuel Institute of Biochemical Physics of Russian Academy of Science, Moscow, Russia
b Computer Center of Russian Academy of Science, Moscow, Russia
c Central State Medical Academy of Department of Presidential Affairs, Moscow, Russia
d City Clinical Hospital No. 51, Moscow, Russia
e Lomonosov Moscow State University, Moscow, Russia
f Institute of Cardiology, Russian Cardiology Scientific and Production Center, Moscow, Russia
g Moscow State University of Medicine and Dentistry named after A.I. Evdokimov, Moscow, Russia
h Sechenov Moscow Medical Academy, Moscow, Russia
i Kazan State Medical University, Kazan, Russia
j Perm State Medical University named after E.A. Vagner, Perm, Russia
k Stavropol State Medical University, Stavropol, Russia
l Rostov State Medical University, Rostov-on-Don, Russia
m Chelyabinsk state medical academy, Chelyabinsk, Russia
n North-Western State Medical University named after Mechnikov, St. Petersburg, Russia
Full-text PDF (548 kB) Citations (8)
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DOI: https://doi.org/10.17537/2016.11.46
Abstract: A predictive model is presented which allows estimating six-month-risk of cardiovascular disease in patients discharged from hospital after acute coronary syndrome. A database, that has been collected from 16 medical centers in seven Russian cities during seven years, was used to create the model. The database contains a wide range of clinical, biochemical and genetic characteristics. The approaches based on the use of optimal partitioning, such as the method of optimal valid partitioning (OVD) and the modified method of statistically weighted syndromes (MSWS), were used in order to create the predictive model. The accuracy of the model is quite well and is estimated by the value of AUC=0.72. This model shows the better predictive ability in comparison with the most widely used methods such as logistic regression, usage of decision trees, neural networks etс.
Key words: acute coronary disease, ischemic heart disease, recognition, collective decision making, optimal partition, prognosis.
Received 14.01.2016, 08.02.2016, Published 23.03.2016
Document Type: Article
UDC: 519.24+004.931+616.12
Language: Russian
Citation: R. R. Guliev, O. V. Senko, D. A. Zateishchikov, V. V. Nosikov, I. V. Uporov, A. V. Kuznetsova, M. A. Evdokimova, S. N. Tereshchenko, E. V. Akatova, M. G. Glaser, A. S. Galyavich, N. A. Koziolova, A. V. Yagoda, O. I. Boeva, S. V. Shlyk, S. Yu. Levashov, V. O. Konstantinov, V. A. Brazhnik, S. D. Varfolomeev, I. N. Kurochkin, “The use of optimal partitionings for multiparameter data analysis in clinical trials”, Mat. Biolog. Bioinform., 11:1 (2016), 46–63
Citation in format AMSBIB
\Bibitem{GulSenZat16}
\by R.~R.~Guliev, O.~V.~Senko, D.~A.~Zateishchikov, V.~V.~Nosikov, I.~V.~Uporov, A.~V.~Kuznetsova, M.~A.~Evdokimova, S.~N.~Tereshchenko, E.~V.~Akatova, M.~G.~Glaser, A.~S.~Galyavich, N.~A.~Koziolova, A.~V.~Yagoda, O.~I.~Boeva, S.~V.~Shlyk, S.~Yu.~Levashov, V.~O.~Konstantinov, V.~A.~Brazhnik, S.~D.~Varfolomeev, I.~N.~Kurochkin
\paper The use of optimal partitionings for multiparameter data analysis in clinical trials
\jour Mat. Biolog. Bioinform.
\yr 2016
\vol 11
\issue 1
\pages 46--63
\mathnet{http://mi.mathnet.ru/mbb250}
\crossref{https://doi.org/10.17537/2016.11.46}
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