Evaluation of the Cardiovascular Risk in Middle-aged Workers: An Artificial Neural Networks-based Approach

A method of the evaluation of the risk of cardiovascular events in the group of middle-aged male workers was developed on the basis of artificial neural networks (ANN). The list of analyzed variables included parameters of allostatic load and signs of myocardial involvement. The results were compare...

Full description

Saved in:
Bibliographic Details
Published inProcedia computer science Vol. 80; pp. 2418 - 2422
Main Authors Sboev, Alexander, Gorokhova, Svetlana, Pfaf, Viktor, Moloshnikov, Ivan, Gudovskikh, Dmitry, Rybka, Roman, Selivanov, Anton, Serenko, Aleksey
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2016
Subjects
cardiovascular risk
data analysis
data science
neural network
data analysis
cardiovascular risk
data science
neural network
Online AccessGet full text

Cover

Abstract A method of the evaluation of the risk of cardiovascular events in the group of middle-aged male workers was developed on the basis of artificial neural networks (ANN). The list of analyzed variables included parameters of allostatic load and signs of myocardial involvement. The results were compared with traditional scales and risk charts (SCORE, PROCAM, and Framingham). A better prognostic value of the proposed model was observed, which makes it reasonable to use both additional markers and ANN.
AbstractList A method of the evaluation of the risk of cardiovascular events in the group of middle-aged male workers was developed on the basis of artificial neural networks (ANN). The list of analyzed variables included parameters of allostatic load and signs of myocardial involvement. The results were compared with traditional scales and risk charts (SCORE, PROCAM, and Framingham). A better prognostic value of the proposed model was observed, which makes it reasonable to use both additional markers and ANN.
Author Rybka, Roman
Sboev, Alexander
Selivanov, Anton
Gorokhova, Svetlana
Serenko, Aleksey
Pfaf, Viktor
Moloshnikov, Ivan
Gudovskikh, Dmitry
Author_xml – sequence: 1
  givenname: Alexander
  surname: Sboev
  fullname: Sboev, Alexander
  email: sag111@mail.ru
  organization: NRC «Kurchatov Institute», Moscow, Russia
– sequence: 2
  givenname: Svetlana
  surname: Gorokhova
  fullname: Gorokhova, Svetlana
  email: cafedra2004@mail.ru
  organization: Research Clinical Center of Russian Railways, Moscow, Russia
– sequence: 3
  givenname: Viktor
  surname: Pfaf
  fullname: Pfaf, Viktor
  email: cafedra2004@mail.ru
  organization: Research Clinical Center of Russian Railways, Moscow, Russia
– sequence: 4
  givenname: Ivan
  surname: Moloshnikov
  fullname: Moloshnikov, Ivan
  organization: NRC «Kurchatov Institute», Moscow, Russia
– sequence: 5
  givenname: Dmitry
  surname: Gudovskikh
  fullname: Gudovskikh, Dmitry
  organization: NRC «Kurchatov Institute», Moscow, Russia
– sequence: 6
  givenname: Roman
  surname: Rybka
  fullname: Rybka, Roman
  organization: NRC «Kurchatov Institute», Moscow, Russia
– sequence: 7
  givenname: Anton
  surname: Selivanov
  fullname: Selivanov, Anton
  organization: NRC «Kurchatov Institute», Moscow, Russia
– sequence: 8
  givenname: Aleksey
  surname: Serenko
  fullname: Serenko, Aleksey
  organization: NRC «Kurchatov Institute», Moscow, Russia
BookMark eNp9kM1OwzAQhC1UJErpE3DxCyRs_uoEiUNUlR-pgIRAHC3HXlOnIa7stIi3x205cGIvsyvNrEbfORn1tkdCLhOIE0hmV228cVb6OA1HDEVc5HBCxknJWAQFVKM_-xmZet9CmKwsq4SNSbvYiW4rBmN7ajUdVkjnwiljd8LLbSccfTF-TU1PH41SHUbiAxV9t26Nzl_Tuqe1G4w20oiOPuHWHWT4CgYfNcIHc70J_YRcXZBTLTqP01-dkLfbxev8Plo-3z3M62Ukc0iGSEKZ6rQRQudNqivFGigxEwWkEosKVZZmChSDnGldagaJUDPGQOhZlqqiwGxCsuNf6az3DjXfOPMp3DdPgO-J8ZYfiPE9MQ4FD8RC6uaYwlBtZ9BxLw32EpVxKAeurPk3_wNf7XjI
CitedBy_id crossref_primary_10_1016_j_ijar_2021_03_002
Cites_doi 10.1007/s10994-006-6226-1
10.1016/j.jjcc.2011.11.005
10.1023/A:1010933404324
10.1214/aos/1013203451
10.1161/CIRCULATIONAHA.112.000412
ContentType Journal Article
Copyright 2016 The Authors
Copyright_xml – notice: 2016 The Authors
DBID 6I.
AAFTH
AAYXX
CITATION
DOI 10.1016/j.procs.2016.05.540
DatabaseName ScienceDirect Open Access Titles
Elsevier:ScienceDirect:Open Access
CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 1877-0509
EndPage 2422
ExternalDocumentID 10_1016_j_procs_2016_05_540
S1877050916310316
GroupedDBID --K
0R~
0SF
1B1
457
5VS
6I.
71M
AACTN
AAEDT
AAEDW
AAFTH
AAIKJ
AALRI
AAQFI
AAXUO
ABMAC
ACGFS
ADBBV
ADEZE
AEXQZ
AFTJW
AGHFR
AITUG
ALMA_UNASSIGNED_HOLDINGS
AMRAJ
E3Z
EBS
EJD
EP3
FDB
FNPLU
HZ~
IXB
KQ8
M41
M~E
NCXOZ
O-L
O9-
OK1
P2P
RIG
ROL
SES
SSZ
AAYXX
ADVLN
AKRWK
CITATION
ID FETCH-LOGICAL-c401t-c082f2baaf4b2f9d7b08e3a502ce59ed323d0d7047ff8f701ad6770af632d55e3
IEDL.DBID IXB
ISSN 1877-0509
IngestDate Fri Aug 23 00:54:40 EDT 2024
Wed May 17 00:58:03 EDT 2023
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Keywords data analysis
cardiovascular risk
data science
neural network
Language English
License This is an open access article under the CC BY-NC-ND license.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c401t-c082f2baaf4b2f9d7b08e3a502ce59ed323d0d7047ff8f701ad6770af632d55e3
OpenAccessLink https://www.sciencedirect.com/science/article/pii/S1877050916310316
PageCount 5
ParticipantIDs crossref_primary_10_1016_j_procs_2016_05_540
elsevier_sciencedirect_doi_10_1016_j_procs_2016_05_540
PublicationCentury 2000
PublicationDate 2016
2016-00-00
PublicationDateYYYYMMDD 2016-01-01
PublicationDate_xml – year: 2016
  text: 2016
PublicationDecade 2010
PublicationTitle Procedia computer science
PublicationYear 2016
Publisher Elsevier B.V
Publisher_xml – name: Elsevier B.V
References Wu, T.-F., & Lin, C.-J. (2004). Probability Estimates for Multi-class Classification by Pairwise Coupling.
Zhu, Zou, Rosset, Hastie (bib0040) 2009
Geurts, Ernst, Wehenkel (bib0025) 2006
Gorokhova, S., Sboev, A., Kukin, K., Rybka, R., Muraseeva, E., & Atkov, O. (2013). The Application of Artificial Neural Networks in the Diagnosis of Coronary Heart Disease.
Allan, Nouri, Koronwyk, Kolber, Vandermeer, McCormack (bib0005) 2013; 127
Breiman (bib0015) 2001
Friedman (bib0020) 2001
45-57.
Atkov, Gorokhova, Sboev, Generozov, Muraseeva, Moroshkina (bib0010) 2012
975-1005.
Breiman (10.1016/j.procs.2016.05.540_bib0015) 2001
10.1016/j.procs.2016.05.540_bib0030
Allan (10.1016/j.procs.2016.05.540_bib0005) 2013; 127
Atkov (10.1016/j.procs.2016.05.540_bib0010) 2012
Zhu (10.1016/j.procs.2016.05.540_bib0040) 2009
Geurts (10.1016/j.procs.2016.05.540_bib0025) 2006
Friedman (10.1016/j.procs.2016.05.540_bib0020) 2001
10.1016/j.procs.2016.05.540_bib0035
References_xml – start-page: 5
  year: 2001
  end-page: 32
  ident: bib0015
  publication-title: Random Forests. Machine Learning
  contributor:
    fullname: Breiman
– start-page: 1189
  year: 2001
  end-page: 1232
  ident: bib0020
  article-title: Greedy Function Approximation: A Gradient Boosting Machine
  publication-title: The Annals of Statistics
  contributor:
    fullname: Friedman
– volume: 127
  start-page: 1948
  year: 2013
  end-page: 1956
  ident: bib0005
  article-title: Agreement Among Cardiovascular Disease Risk Calculators
  publication-title: Circulation
  contributor:
    fullname: McCormack
– start-page: 190
  year: 2012
  end-page: 194
  ident: bib0010
  article-title: Coronary heart disease diagnosis by artificial neural networks including genetic polymorphisms and clinical parameters
  publication-title: J Cardiol.
  contributor:
    fullname: Moroshkina
– start-page: 3
  year: 2006
  end-page: 42
  ident: bib0025
  article-title: Extremely randomized trees
  publication-title: Machine Learning
  contributor:
    fullname: Wehenkel
– start-page: 349
  year: 2009
  end-page: 360
  ident: bib0040
  publication-title: Multi-class AdaBoost. Stat Interface
  contributor:
    fullname: Hastie
– start-page: 3
  year: 2006
  ident: 10.1016/j.procs.2016.05.540_bib0025
  article-title: Extremely randomized trees
  publication-title: Machine Learning
  doi: 10.1007/s10994-006-6226-1
  contributor:
    fullname: Geurts
– start-page: 190
  year: 2012
  ident: 10.1016/j.procs.2016.05.540_bib0010
  article-title: Coronary heart disease diagnosis by artificial neural networks including genetic polymorphisms and clinical parameters
  publication-title: J Cardiol.
  doi: 10.1016/j.jjcc.2011.11.005
  contributor:
    fullname: Atkov
– start-page: 5
  year: 2001
  ident: 10.1016/j.procs.2016.05.540_bib0015
  publication-title: Random Forests. Machine Learning
  doi: 10.1023/A:1010933404324
  contributor:
    fullname: Breiman
– start-page: 349
  year: 2009
  ident: 10.1016/j.procs.2016.05.540_bib0040
  publication-title: Multi-class AdaBoost. Stat Interface
  contributor:
    fullname: Zhu
– start-page: 1189
  year: 2001
  ident: 10.1016/j.procs.2016.05.540_bib0020
  article-title: Greedy Function Approximation: A Gradient Boosting Machine
  publication-title: The Annals of Statistics
  doi: 10.1214/aos/1013203451
  contributor:
    fullname: Friedman
– volume: 127
  start-page: 1948
  year: 2013
  ident: 10.1016/j.procs.2016.05.540_bib0005
  article-title: Agreement Among Cardiovascular Disease Risk Calculators
  publication-title: Circulation
  doi: 10.1161/CIRCULATIONAHA.112.000412
  contributor:
    fullname: Allan
– ident: 10.1016/j.procs.2016.05.540_bib0030
– ident: 10.1016/j.procs.2016.05.540_bib0035
SSID ssj0000388917
Score 2.0660741
Snippet A method of the evaluation of the risk of cardiovascular events in the group of middle-aged male workers was developed on the basis of artificial neural...
SourceID crossref
elsevier
SourceType Aggregation Database
Publisher
StartPage 2418
SubjectTerms cardiovascular risk
data analysis
data science
neural network
Title Evaluation of the Cardiovascular Risk in Middle-aged Workers: An Artificial Neural Networks-based Approach
URI https://dx.doi.org/10.1016/j.procs.2016.05.540
Volume 80
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3NS8MwFA9jXrz4Lc6PkYNHw9ImbVpvdWwMxzxMh7uFdEmgE7rh5v9vXtoOB-LBU2nJo-WX9H3x3u8hdK81VS5K0CSNhAtQtAtQ0lgbYilTnHPrTgH0Dk9e4tGMP8-jeQv1m14YKKusdX-l0722rp_0ajR766LovQaJEMBe4jwKmFUAtNssCnwT3_xpl2cBtpPUD96F9QQEGvIhX-YFdgJou4MYGDx9EuQ3A_XD6AxP0FHtLeKs-qBT1DLlGTpuJjHg-sc8R8vBjrQbryx2Th3u7xWa4mmx-cBFiSc-IUGcFtEYEuXO-3vEWelfUZFJYODr8BdfIL4hYOg0zmry8Qs0Gw7e-iNST1EgCxc7bcnCGXkb5kpZnoc21SKniWEqoiF0YBnNQqapFpQLaxMr3N7o2AGrbMxCHUWGXaJ2uSrNFcLcGJ4EPE9NrjlloWJxomMjDNcq5AvRQQ8NdHJdkWXIpopsKT3SEpCWNJIO6Q6KG3jl3p5Lp87_Erz-r-ANOoS7KoVyi9rbzy9z55yKbd5FB9l4-j7u-tPzDZBjzQc
link.rule.ids 315,783,787,3513,4031,27935,27936,27937,45886
linkProvider Elsevier
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3NT8IwFG8QD3rx24ifPXi0oWxdu3lDIgEFDgoJt6ajbTJMBhH8_-3rNiKJ8eBpyZaXLb--va-893sI3WtNlcsSNEki4RIU7RKUhGtDLA0VY8w6LYDZ4eGI9ybsZRpNa6hTzcJAW2Vp-wub7q11eadZotlcZlnzvRULAewlLqKAXQV8B-3C2CWoeX_6tCm0AN1J4jfvggABiYp9yPd5gaMA3u4WBwpPXwX5zUP98DrdI3RQhou4XXzRMaqZ_AQdVqsYcPlnnqL584a1Gy8sdlEd7mx1muK3bPWBsxwPfUWCODOiMVTKXfj3iNu5f0XBJoGBsMNffIf4ioCn07hdso-foUn3edzpkXKNApm55GlNZs7L2yBVyrI0sIkWKY1NqCIawAiW0WEQaqoFZcLa2Ap3OJo7ZJXlYaCjyITnqJ4vcnOBMDOGxS2WJibVjIaBCnmsuRGGaRWwmWighwo6uSzYMmTVRjaXHmkJSEsaSYd0A_EKXrl16NLZ878EL_8reIf2euPhQA76o9crtA9PinrKNaqvP7_MjYsw1umt16BvlwLOkg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Evaluation+of+the+Cardiovascular+Risk+in+Middle-aged+Workers%3A+An+Artificial+Neural+Networks-based+Approach&rft.jtitle=Procedia+computer+science&rft.au=Sboev%2C+Alexander&rft.au=Gorokhova%2C+Svetlana&rft.au=Pfaf%2C+Viktor&rft.au=Moloshnikov%2C+Ivan&rft.date=2016&rft.pub=Elsevier+B.V&rft.issn=1877-0509&rft.eissn=1877-0509&rft.volume=80&rft.spage=2418&rft.epage=2422&rft_id=info:doi/10.1016%2Fj.procs.2016.05.540&rft.externalDocID=S1877050916310316
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1877-0509&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1877-0509&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1877-0509&client=summon