EconPapers    
Economics at your fingertips  
 

INTEGRATING ARTIFICIAL NEURAL NETWORKS FOR DEVELOPING TELEMEDICINE SOLUTION

Mihaela Gheorghe ()
Additional contact information
Mihaela Gheorghe: Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies, Romania

Scientific Bulletin - Economic Sciences, 2015, vol. 14, issue 1, pages 64-69

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.

Keywords: telemedicine; neural networks; machine learning; medical diagnosis; artificial intelligence. (search for similar items in EconPapers)
JEL-codes: C6 C8 I1 (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://economic.upit.ro/repec/pdf/2015_1_8.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:pts:journl:y:2015:i:1:p:64-69

Access Statistics for this article

Scientific Bulletin - Economic Sciences is currently edited by Logica Banica

More articles in Scientific Bulletin - Economic Sciences from University of Pitesti Contact information at EDIRC.
Series data maintained by Logica Banica ().

 
Page updated 2015-09-08
Handle: RePEc:pts:journl:y:2015:i:1:p:64-69