Issue 1 (187), article 5

DOI: https://doi.org/10.15407/kvt187.01.067

Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.67-80

Kovalenko A.S., Dr Medicine, Prof., Head of Department of Medical Information Systems
e-mail: askov49@gmail.com
Kozak L.M., Dr Biology, Leading Researcher of Department of Medical Information Systems
e-mail: lmkozak52@gmail.com
Romanyuk O.A., Junior Researcher of Department of Medical Information Systems
e-mail: ksnksn7@gmail.com

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine

INFORMATION TECHNOLOGY FOR DIGITAL MEDICINE

Introduction. The need of health care institutions in the repeated use of digital medical images by different specialists during patient care and long-term storage for the analysis of diagnostic information determines the relevance of this work. The need for means and methods of storage of digital medical data with their subsequent processing and analysis, as well as on mobile devices for the collection, digital data processing and exchange increase.

The purpose of the article is to analyze the experience of creating medical information systems, the development of information technology support the storage and processing of digital medical information and the further development of information technology for digital medicine.

Results. Employees of the department of medical information systems for more than 20 years of activities of the International Research and Training Centre for Information Technologies and Systems NAS and MES of Ukraine solved the problem of constructing the medical information systems and information diagnostics technologies with the use of electronic medical records, methods and means of the mathematical analysis of medical data. The developed technology support for storing and processing digital medical information combines into a single functional network the medical information system, instrumental diagnostic systems and a system of conservation and archiving digital medical images. PACS and cloud technologies was used for long-term storage of digital medical images.

Conclusion. Organization of long-term storage of digital medical images obtained from the diagnostic systems in health care facilities, and the ability to use this information by doctors at their workplace in the current diagnostic and treatment process was provided by using the developed information technology support for storing and processing digital medical information.

Keywords: medical information system, information technology, digital medical imaging, long-term storage.

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REFERENCE

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Recieved 27.12.2016

Issue 185, article 6

DOI:https://doi.org/10.15407/kvt185.03.060

KVT, 2016, Issue 185, pp.60-76

UDC 617.751-057-07

THE ASSESMENT OF CONNECTION STRUCTURE BETWEEN THE FUNCTIONAL INDEXES OF PC OPERATORS DURING THE VISUAL WORK WITH FACTOR MODELS’ USE

Evtushenko A.S.1, Kozak L.M.2, Kochina M.L.3

1Kharkiv Municipal Clinical Hospital №14 named by Prof. L.L. Girshman, Kharkiv, Ukraine

2International Reasearch and Training Center for Information Technologies and Systems of National Academy of Science and Ministry of Science of Ukraine, Kyiv, Ukraine

3Kharkiv Medical Academy of Postgraduate Education, Kharkiv, Ukraine

andrey-eye@yandex.ru , lmkozak52@gmail.com , m_kochina@yahoo.com

Introduction. PC operators’ work is connected to necessity of information large amounts perception from PC display. Such activities require of high attention concentration and particular responsibility for production goals. Arduous visual work of PC operators on close distance results in high psychoemotional stress and exerts an impact on functional state. Severe visual asthenopias in PC operators may be observed on the background of normal values of visual system’s functional indexes that require of such states causes determination for prophylaxis measures development.

The purpose of the article is to evaluate the impact of the visual work at close distance on the structure of relationships between visual system’s indexes and functional state’s indexes.

Methods. 41 PC operators took part in the study. The average age of study subjects was (29,6 ± 4,0) y.o. The functional indexes of visual system were measured in all PC operators before and after visual work. The indexes of functional state were also measured by self-assessment using developed questionnaire. The obtained results processing was performed using descriptive statistics methods, cluster and factor analysis.

Results. On the background of performed research using clustering and factor analysis it was found that younger PC operators with higher visual functions the visual work on close distance results in state similar to spasm of accommodation. The recovery after night rest was worse than in PC operators with low visual functions. Older PC operators have higher quality of recovery after night rest. It may be determined by development of visual fatigue as the result of visual work . The recovery after night rest in case of visual fatigue is better than in case of accommodation spasm.

Conclusion. Visual work on close distance results in configuration change of connection between indexes of visual system that support visual perception. The peculiarities of these changes depend on visual system’s indexes. The results of PC operators functional state’s self-assessment using the questionnaire developed by us had shown that in PC operators with low functional possibilities the common and visual complaints rate was certainly lower than in operators with high functional possibilities.

Keywords: factor models, visual system, functional state, PC operator work.

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References:

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Received 20.05.16

Issue 184, article 5

DOI:https://doi.org/10.15407/kvt184.02.056

KVT, 2016, Issue 184, pp.56-72

UDC 004.75+004.932.2:616

INFORMATION SUPPORT FOR INTEROPERABILITY OF INSTRUMENTAL DIAGNOSTIC SYSTEMS AND LONG-TERM STORAGE SYSTEM OF DIGITAL MEDICAL IMAGES IN HEALTH CARE INSTITUTIONS

Romanyuk O.A., Kovalenko A.S., Kozak L.M.

International Research and Training Center for Information Technologies and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

ksnksn7@gmail.com , askov49@gmail.com , lmkozak52@gmail.com

 

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Introduction. The need of health care institutions in the repeated use of digital medical images by different specialists during patient care and long-term storage for the analysis of diagnostic information determines the relevance of this work.

The purpose of the article is to form technique for adapting the system of transmission and archiving of digital medical images according to the conditions of the health care institution.

Results. Analysis of medical image storage systems to select the specific software implementation according to the requirements of a particular medical institution was held. After testing and validation in working conditions PACS Conquest DICOM has been selected, its functionality has been verified. The technique of adapting the system for transmission and archiving of digital medical images has been developed, which includes an analysis of instrumental studies systems, installation of database components and configuration of PACS Conquest DICOM-server, connecting the instrumental studies systems and organization of access to digital medical images for medical personnel. Testing of the proposed technique was carried out at the National Institute of Cardiovascular Surgery named by N. Amosov.

Conclusion. The possibility of implementation the free and multi-platform storage system with connection of multiple diagnostic systems for efficient analysis of DMC on each workstation and long-term storage DMC is provided as a result of using the proposed technique.

Keywords: digital medical imaging, standard DICOM, long-term storage.

References:

  1. Kamenshchikov A.A. Interoperability in the field of e-health. Information Technologies and Computing Systems, 2009, № 5, pp. 67–71(in Russian).
  2. Robert Hoyt, Nora Bailey, Ann Yoshihashi. Health Informatics: Practical Guide for Healthcare and Information Technology Professionals (5th ed.). New York.: Lulu.com, 2012, 492p.
  3. EN ISO 12052:2011. Health informatics. Digital imaging and communication in medicine (DICOM) including workflow and data management. Available at: http://iso.org
  4. Oosterwijk Herman. DICOM Basics (3rd ed.). O Tech, 2005, pp. 23–28.
  5. Oosterwijk Herman. PACS Fundamentals (2nd ed.). O Tech, 2004, pp. 25–44.
  6. Dreyer K.J., Hirschorn D.S., Thrall J.H. PACS: A Guide to the Digital Revolution. London.: Springer, 2010, 596p., pp.249–269.

Received 15.12.2015

Issue 182, article 7

DOI:https://doi.org/10.15407/kvt182.02.084

Kibern. vyčisl. teh., 2015, Issue 182, pp.

Krivova O.A., Kozak L.M.

International Research and Training Center for Information Technologies and
Systems of the National Academy of Sciences of Ukraine and Ministry of Education
and Science of Ukraine (Kiev)

СOMPLEX ESTIMATION OF REGIONAL DEMOGRAPHIC DEVELOPMENT

Introduction. Several studies are being conducted in the world to measure developmental disparities between countries, regions and territorial units. Composite indicators (or indexes) are used whenever a lot of variables are needed for evaluating developmental disparities between territories. Demographic variables are considered as important indicators of socio-economic development of regions. We show how cluster analysis can be combined with elements of multicriteria decision analysis (MCDA) to construct composite index regional demographic development of Ukraine.
The purpose of this article is the development of regional socioeconomic systems analysis methodology and construction of composite indicators of regional demographic development.
Results. We have used 5 territorial social-demographic indicators: 1) total fertility rate; 2) death rate of children under age of five; 3) life expectation at birth; 4) survivorship probabilities for men from 20 to 65 years; 5) survivorship probabilities for women from 20 to 65 years. The following strategy can be pursued in order to construct composite index . First, a cluster analysis (algorithms Ward and K-means) for defining clusters of regions based on the value of the individual indicators is used. The result of the cluster analysis is typological clusters of the selected regions. Second, such as each cluster can be characterized with a centroid, these centroids must be ordered from best to worst. Weights of composite index are calculated as coefficients of the best linear regression model of preference function.
Conclusion. The composite index of regional demographic development allows to assess the degree of variance in regional demographic development and ranking of regions.
Keywords: clustering, a composite indicator, the index of regional demographic development, ordered classification.

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References

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Received 01.06.2015