Standard
Finding motifs in medical data. / Osipov, Vasily; Vodyaho, Alexander; Stankova, Elena; Zukova, Nataly; Zeno, Bassel.
Computational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017. ed. / Ana Maria A.C. Rocha; Elena Stankova; Sanjay Misra; Giuseppe Borruso; Alfredo Cuzzocrea; David Taniar; Osvaldo Gervasi; Beniamino Murgante; Carmelo M. Torre; Bernady O. Apduhan. Springer Nature, 2017. p. 371-386 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10408 LNCS).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Harvard
Osipov, V, Vodyaho, A
, Stankova, E, Zukova, N & Zeno, B 2017,
Finding motifs in medical data. in AMAC Rocha, E Stankova, S Misra, G Borruso, A Cuzzocrea, D Taniar, O Gervasi, B Murgante, CM Torre & BO Apduhan (eds),
Computational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10408 LNCS, Springer Nature, pp. 371-386, 17th International Conference on Computational Science and Its Applications, ICCSA 2017, Trieste, Italy,
2/07/17.
https://doi.org/10.1007/978-3-319-62404-4_27APA
Osipov, V., Vodyaho, A.
, Stankova, E., Zukova, N., & Zeno, B. (2017).
Finding motifs in medical data. In A. M. A. C. Rocha, E. Stankova, S. Misra, G. Borruso, A. Cuzzocrea, D. Taniar, O. Gervasi, B. Murgante, C. M. Torre, & B. O. Apduhan (Eds.),
Computational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017 (pp. 371-386). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10408 LNCS). Springer Nature.
https://doi.org/10.1007/978-3-319-62404-4_27Vancouver
Osipov V, Vodyaho A
, Stankova E, Zukova N, Zeno B.
Finding motifs in medical data. In Rocha AMAC, Stankova E, Misra S, Borruso G, Cuzzocrea A, Taniar D, Gervasi O, Murgante B, Torre CM, Apduhan BO, editors, Computational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017. Springer Nature. 2017. p. 371-386. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
https://doi.org/10.1007/978-3-319-62404-4_27Author
Osipov, Vasily ; Vodyaho, Alexander
; Stankova, Elena ; Zukova, Nataly ; Zeno, Bassel. /
Finding motifs in medical data. Computational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017. editor / Ana Maria A.C. Rocha ; Elena Stankova ; Sanjay Misra ; Giuseppe Borruso ; Alfredo Cuzzocrea ; David Taniar ; Osvaldo Gervasi ; Beniamino Murgante ; Carmelo M. Torre ; Bernady O. Apduhan. Springer Nature, 2017. pp. 371-386 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
BibTeX
@inproceedings{2537ec1fe6dc4fd7a01b6e6a2931c425,
title = "Finding motifs in medical data",
abstract = "Nowadays big volumes of medical data are accumulated. So the problem of analysis of these data and mining linked logical structures, defining internal data semantics is an actual one. Solution of this problem allows solve the problem of optimizing intelligent context search. In the article an approach for solving this problem for analyzing processes running in human organism is discussed. Suggested approach is based on building of linked logical structures and assumes finding of motifs in variations of parameters of systems and subsystems. An algorithm of finding of motifs is suggested. The result of algorithm operation is logical structure that reflects internal dependencies which exist in human organism. Nowadays suggested approach is used in Almazov Cardio-logical Center for medical data processing.",
keywords = "Context search, Linked logical structure, Medical data, Motifs",
author = "Vasily Osipov and Alexander Vodyaho and Elena Stankova and Nataly Zukova and Bassel Zeno",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference date: 02-07-2017 Through 05-07-2017",
year = "2017",
doi = "10.1007/978-3-319-62404-4_27",
language = "English",
isbn = "9783319624037",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "371--386",
editor = "Rocha, {Ana Maria A.C.} and Elena Stankova and Sanjay Misra and Giuseppe Borruso and Alfredo Cuzzocrea and David Taniar and Osvaldo Gervasi and Beniamino Murgante and Torre, {Carmelo M.} and Apduhan, {Bernady O.}",
booktitle = "Computational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017",
address = "Germany",
}
RIS
TY - GEN
T1 - Finding motifs in medical data
AU - Osipov, Vasily
AU - Vodyaho, Alexander
AU - Stankova, Elena
AU - Zukova, Nataly
AU - Zeno, Bassel
N1 - Conference code: 17
PY - 2017
Y1 - 2017
N2 - Nowadays big volumes of medical data are accumulated. So the problem of analysis of these data and mining linked logical structures, defining internal data semantics is an actual one. Solution of this problem allows solve the problem of optimizing intelligent context search. In the article an approach for solving this problem for analyzing processes running in human organism is discussed. Suggested approach is based on building of linked logical structures and assumes finding of motifs in variations of parameters of systems and subsystems. An algorithm of finding of motifs is suggested. The result of algorithm operation is logical structure that reflects internal dependencies which exist in human organism. Nowadays suggested approach is used in Almazov Cardio-logical Center for medical data processing.
AB - Nowadays big volumes of medical data are accumulated. So the problem of analysis of these data and mining linked logical structures, defining internal data semantics is an actual one. Solution of this problem allows solve the problem of optimizing intelligent context search. In the article an approach for solving this problem for analyzing processes running in human organism is discussed. Suggested approach is based on building of linked logical structures and assumes finding of motifs in variations of parameters of systems and subsystems. An algorithm of finding of motifs is suggested. The result of algorithm operation is logical structure that reflects internal dependencies which exist in human organism. Nowadays suggested approach is used in Almazov Cardio-logical Center for medical data processing.
KW - Context search
KW - Linked logical structure
KW - Medical data
KW - Motifs
UR - http://www.scopus.com/inward/record.url?scp=85026758068&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-62404-4_27
DO - 10.1007/978-3-319-62404-4_27
M3 - Conference contribution
AN - SCOPUS:85026758068
SN - 9783319624037
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 371
EP - 386
BT - Computational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017
A2 - Rocha, Ana Maria A.C.
A2 - Stankova, Elena
A2 - Misra, Sanjay
A2 - Borruso, Giuseppe
A2 - Cuzzocrea, Alfredo
A2 - Taniar, David
A2 - Gervasi, Osvaldo
A2 - Murgante, Beniamino
A2 - Torre, Carmelo M.
A2 - Apduhan, Bernady O.
PB - Springer Nature
T2 - 17th International Conference on Computational Science and Its Applications, ICCSA 2017
Y2 - 2 July 2017 through 5 July 2017
ER -
