Development of multi-agent system of neural network diagnostics and remote monitoring of patient

Authors

DOI:

https://doi.org/10.15587/1729-4061.2016.75690

Keywords:

medical diagnostics, neural network classification, remote monitoring, organizational multi-agent system

Abstract

The system of medical diagnostics and remote monitoring based on the example of skin diseases was developed. The diagnostics is carried out by a group of multilayer perceptrons on the basis of processing the images of the explored object and medical registration data. The application of high-performance computing made it possible to carry out remote control of the state of the observed object by the change of its image in  real time.

For the implementation of the indicated system, a generalized model of the process of neural network diagnostics and monitoring was developed. The distinctive features of this model are the combination of machine training and agent technologies, which allows, firstly, using results of the remote monitoring for making a diagnosis; secondly, using simultaneously the totality of methods and means of collection, storage, processing, analysis and transmission of a video stream or a single image for solving the problems of decision making based on image processing.

The multi-agent organizational structure of the components of the proposed model was designed. The organizational structure is characterized by the formed aggregation levels, as well as by the possibility to dynamically distribute the roles among the agents. Such organization makes it possible to adapt for managing the following incidents: monitoring the state of health, making diagnosis and medical aid.

Author Biography

Natalia Axak, Kharkiv National University of Radio Electronics Nauki ave., 14, Kharkiv, Ukraine, 61166

PhD, Associate Professor

Department of Electronic Computers

References

  1. Kang, K.-W., Chang, H.-J., Shim, H., Kim, Y.-J., Choi, B.-W., Yang, W.-I. et. al. (2012). Feasibility of an automatic computer-assisted algorithm for the detection of significant coronary artery disease in patients presenting with acute chest pain. European Journal of Radiology, 81 (4), 640–646. doi: 10.1016/j.ejrad.2012.01.017
  2. Levin, S. R., Harley, E. T., Fackler, J. C., Lehmann, C. U., Custer, J. W., France, D., Zeger, S. L. (2012). Real-time forecasting of pediatric intensive care unit length of stay using computerized provider orders. Critical Care Medicine, 40 (11), 3058–3064. doi: 10.1097/ccm.0b013e31825bc399
  3. Wiens, J., Guttag, J. V., Horvitz, E. (2012). Patient risk stratification for hospital–associated c. diff as a time–series classification task. Advances in Neural Information Systems, 467–475.
  4. Kohn, M. S., Skarulis, P. C. (2012). IBM Watson Delivers New Insights for Treatment and Diagnosis Digital Health Conf., presentation.
  5. Chakraborty, S., Gupta, S. (2014). Medical Application Using Multi Agent System – A Literature Survey. Journal of Engineering Research and Applications, 4 (2), 528–546.
  6. Nedz'ved', A. M., Ablameyko, S. V. (2013). Intellektual'noye programmnoye obespecheniye analiza izobrazheniy, adaptiruyemoye k zadacham meditsinskoy diagnostiki. Vestnik BGU. Ser. 1, 1, 51–56.
  7. Nedz'ved', A. M., Ablameyko, S. V. (2012). Analiz izobrazheniy dlya resheniya zadach meditsinskoy diagnostiki. Minsk: OIPI NAN Belarusi, 240.
  8. Nedz'ved', A. M., Lukashevich, P. V., Belotserkovskiy, A. M. (2013). Gibkaya sistema obrabotki izobrazheniy na baze skript–yadra s ispol'zovaniyem intellektual'nogo agenta. Iskusstvennyy intellekt, 61, 200–208.
  9. Axak, N. G., Korgut, S. A., Novosel'tsev, I. V. (2013). Mul'tiagentnaya model' adaptatsii meditsinskogo Internet–resursa na osnove informatsionnogo portreta pol'zovatelya. Sistemi obrobki ínformatsii, 2 (109), 242–246.
  10. Axak, N. G., Tykhun, A. Yu., Barkovskaya, O. Yu., Soldatov, A. S. (2009). Raspoznavaniye izobrazheniy antropomorfnogo ob"yekta. Bionika intellekta, 1 (70), 102–105.
  11. Blanchet, G., Charbit, M. (2006). Digital signal and image processing using MATLAB. Wiley–ISTE, 764.
  12. Novosel'tsev, I. V., Axak, N. G. (2010). Pokazateli effektivnosti neirosetevoy sistemu meditsinskoy diagnostiki. Sistemi upravlinnya, navigazii ta zv’yazku, 4 (16), 142–149.
  13. Deloach, S. A. (2006). Engineering organization–based multiagent systems. Software Engineering for Multi–Agent Systems IV, 109–125. doi: 10.1007/11738817_7
  14. DeLoach, S. A., Oyenan, W. H., Matson, E. T. (2007). A capabilities-based model for adaptive organizations. Autonomous Agents and Multi-Agent Systems, 16 (1), 13–56. doi: 10.1007/s10458-007-9019-4

Downloads

Published

2016-08-31

How to Cite

Axak, N. (2016). Development of multi-agent system of neural network diagnostics and remote monitoring of patient. Eastern-European Journal of Enterprise Technologies, 4(9(82), 4–11. https://doi.org/10.15587/1729-4061.2016.75690

Issue

Vol. 4 No. 9(82) (2016): Information and controlling system

Section

Information and controlling system

License

Copyright (c) 2016 Natalia Axak

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.