TY - JOUR

T1 - Data consolidation and analysis system for brain research

AU - Volosnikov, Vladislav

AU - Korkhov, Vladimir

AU - Voronchov, Andrey

AU - Gribkov, Kirill

AU - Degtyarev, Alexander

AU - Bogdanov, Alexander

AU - Zalutskaya, Natalia

AU - Neznanov, Nikolay

AU - Ananyeva, Natalia

PY - 2018/12/30

Y1 - 2018/12/30

N2 - Comprehensive studies in the field of brain pathology require strong information support for theconsolidation of data from different sources. The heterogeneity of data sources and the resourceintensive nature of preprocessing make it difficult to conduct comprehensive interdisciplinaryresearch. To solve this problem for brain studies, an information system with unified access toheterogeneous data is required. Effective implementation of such a system requires adaptingpreprocessing methods and creating a model for combining disparate data into a single informationenvironment. We analyze the possibilities and methods of consolidation of clinical and biological data,build a model for the consolidation and interaction of heterogeneous data sources for brain research,implement the model as a cloud service, and provide a data interface in a format encapsulating acomplex architecture from the user. We present the design and implementation of an informationsystem; we show and discuss the results of the application of cluster analysis methods to differentiatevarious types of dementia with MRI data. Our results show that a study of the properties of clusteranalysis data can significantly help neurophysiologists in the study of cognitive disorders such asAlzheimer’s disease, especially with the possibilities provided by the proposed information system.

AB - Comprehensive studies in the field of brain pathology require strong information support for theconsolidation of data from different sources. The heterogeneity of data sources and the resourceintensive nature of preprocessing make it difficult to conduct comprehensive interdisciplinaryresearch. To solve this problem for brain studies, an information system with unified access toheterogeneous data is required. Effective implementation of such a system requires adaptingpreprocessing methods and creating a model for combining disparate data into a single informationenvironment. We analyze the possibilities and methods of consolidation of clinical and biological data,build a model for the consolidation and interaction of heterogeneous data sources for brain research,implement the model as a cloud service, and provide a data interface in a format encapsulating acomplex architecture from the user. We present the design and implementation of an informationsystem; we show and discuss the results of the application of cluster analysis methods to differentiatevarious types of dementia with MRI data. Our results show that a study of the properties of clusteranalysis data can significantly help neurophysiologists in the study of cognitive disorders such asAlzheimer’s disease, especially with the possibilities provided by the proposed information system.

KW - brain

KW - data analysis

KW - data consolidation

KW - cluster analysis

KW - information system

KW - neuroinformatics

KW - Alzheimer’s disease

KW - cloud computing

KW - service-oriented architecture

M3 - Conference article

VL - 2267

SP - 388

EP - 392

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 8th International Conference "Distributed Computing and Grid-Technologies in Science and Education", GRID 2018

Y2 - 10 September 2018 through 14 September 2018

ER -