DocumentCode
2487709
Title
Artificial neural networks for non-invasive chromosomal abnormality screening of fetuses
Author
Neocleous, C.K. ; Nicolaides, K.H. ; Neokleous, K.C. ; Schizas, C.N.
Author_Institution
Dept. of Mech. Eng., Cyprus Univ. of Technol., Lemesos, Cyprus
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
4
Abstract
A large number of different neural network structures have been constructed, trained and tested to a large data base of pregnant women characteristics, aiming at generating a classifier-predictor for the presence of chromosomal abnormalities in fetuses, namely the Trisomy 21 (Down syndrome), Trisomy 18 (Edwards syndrome), Trisomy 13 (Patau syndrome) and the Turner syndrome.
Keywords
cellular biophysics; medical computing; medical disorders; neural nets; obstetrics; Edwards syndrome; Patau syndrome; Trisomy 13; Trisomy 18; Trisomy 21; Turner syndrome; artificial neural network; classifier-predictor; down syndrome; fetuse; neural network structure; noninvasive chromosomal abnormality screening; pregnant women characteristics; Medical diagnostic imaging; Sensitivity;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location
Barcelona
ISSN
1098-7576
Print_ISBN
978-1-4244-6916-1
Type
conf
DOI
10.1109/IJCNN.2010.5596357
Filename
5596357
Link To Document