IDEAS home Printed from https://ideas.repec.org/a/pts/journl/y2015i1p64-69.html
   My bibliography  Save this article

Integrating Artificial Neural Networks For Developing Telemedicine Solution

Author

Listed:
  • Mihaela GHEORGHE

    (Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies, Romania)

Abstract

Artificial intelligence is assuming an increasing important role in the telemedicine field, especially neural networks with their ability to achieve meaning from large sets of data characterized by lacking exactness and accuracy. These can be used for assisting physicians or other clinical staff in the process of taking decisions under uncertainty. Thus, machine learning methods which are specific to this technology are offering an approach for prediction based on pattern classification. This paper aims to present the importance of neural networks in detecting trends and extracting patterns which can be used within telemedicine domains, particularly for taking medical diagnosis decisions.

Suggested Citation

  • Mihaela GHEORGHE, 2015. "Integrating Artificial Neural Networks For Developing Telemedicine Solution," Scientific Bulletin - Economic Sciences, University of Pitesti, vol. 14(1), pages 64-69.
    • Handle: RePEc:pts:journl:y:2015:i:1:p:64-69
    as

    Download full text from publisher

    File URL: http://economic.upit.ro/repec/pdf/2015_1_8.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    telemedicine; neural networks; machine learning; medical diagnosis; artificial intelligence.;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • I1 - Health, Education, and Welfare - - Health

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pts:journl:y:2015:i:1:p:64-69. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alina Hagiu (email available below). General contact details of provider: https://edirc.repec.org/data/fepitro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.