Skip to main content
SpringerLink
Log in

Information-Analytical Systems for Assessing the Rehabilitation of the Patients with Endocrine Diseases

  • Conference paper
  • First Online:
Advances in Human Factors and Ergonomics in Healthcare and Medical Devices (AHFE 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1205))

Included in the following conference series:

  • 941 Accesses

Abstract

Assessing the body’s reserves (rehabilitation potential) to predict the risk of developing diseases or their outcomes (rehabilitation prognosis) is very important. This provides an opportunity for an individual approach to the patient. The proposed method for assessing the basic component of the rehabilitation potential - the morpho-functional index (MFI), developed using computer modeling methods, allows you to obtain accurate (quantitative) and objective information about the state of the human body at the starting point of the examination and to monitor the course of the process in dynamics. The effectiveness of the use of the MFI indicator is confirmed by examples of its use in clinical practice.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. A comprehensive Japanese genetic variation database. About togovar [Electronic resource]. https://togovar.biosciencedbc.jp/doc/about. Accessed 14 Oct 2019

  2. Madani, A., et al.: Fast and accurate view classification of echocardiograms using deep learning. NPJ Digital Med. 1(1), 6 (2018). https://doi.org/10.1038/s41746-017-0013-1

    Article  Google Scholar 

  3. CardioQVARK: Презентация проекта [Электронный ресурс]. http://cardioqvark.ru/netcat_files/16/38/CQ_prezentaciya_A4.pdf. Accessed 14 Oct 2019

  4. Myomo, Inc. [Electronic resource]. http://myomo.com. Accessed 14 Oct 2019

  5. Zhao, Y., et al.: Enabling people with visual impairments to navigate virtual reality with a haptic and auditory cane simulation. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, p. 116. ACM (2018)

    Google Scholar 

  6. Kurnikova, I.A., Kurnikova’s method for determining the biological component of the rehabilitation potential of patients with diabetes [Electronic resource], Freepatent - information and reference portal. http://www.freepatent.ru/patents/2344751. Accessed 14 Oct 2019

Download references

Author information

Authors and Affiliations

  1. Department of therapy and endocrinology, RUDN University, Miklukho-Maklaya Street 6, 117198, Moscow, Russia

    Irina Kurnikova, Sofia Buturlina, Ramchandra Sargar & Artyom Yurovsky

  2. Clinical Hospital of Civil Aviation, Ivankovo Highway, 7, 125367, Moscow, Russia

    Irina Kurnikova, Natalia Zabrodina & Artyom Yurovsky

Authors
  1. Irina Kurnikova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sofia Buturlina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramchandra Sargar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Natalia Zabrodina
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Artyom Yurovsky
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Irina Kurnikova .

Editor information

Editors and Affiliations

  1. Department of Pathology, College of Medicine, Royal University Hospital, University of Saskatchewan, Saskatoon, SK, Canada

    Jay Kalra

  2. Center for Applied Systems Engineering, Veterans Affairs, Indianapolis, IN, USA

    Nancy J. Lightner

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kurnikova, I., Buturlina, S., Sargar, R., Zabrodina, N., Yurovsky, A. (2020). Information-Analytical Systems for Assessing the Rehabilitation of the Patients with Endocrine Diseases. In: Kalra, J., Lightner, N. (eds) Advances in Human Factors and Ergonomics in Healthcare and Medical Devices. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1205. Springer, Cham. https://doi.org/10.1007/978-3-030-50838-8_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-50838-8_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50837-1

  • Online ISBN: 978-3-030-50838-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation