Use of artificial neural networks for clinical diagnosis

G. Papadourakis, M. Vourkas, S. Micheloyannis and B. Jervis

Mathematics and Computers in Simulation (MATCOM), 1996, vol. 40, issue 5, 623-635

Abstract: The application of two unsupervised Artificial Neural Networks (ART2 and Kohonen) for the classification of patients in three medical fields is considered. In the first case, data obtained from spectral analysis of the EEG signals are used in order to detect brain disfunction of persons exposed to organic solvents. The Contingent Negative variation which is an Evoked Response is utilized in the last two cases for the diagnosis of Huntingdon's Disease and for the separation of schizophrenic subtypes.

Date: 1996
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0378475496000110
Full text for ScienceDirect subscribers only

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: https://EconPapers.repec.org/RePEc:eee:matcom:v:40:y:1996:i:5:p:623-635

DOI: 10.1016/0378-4754(96)00011-0

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().