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
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;
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6916-1
DOI :
10.1109/IJCNN.2010.5596357
