DocumentCode
1741304
Title
Neural networks trained with simulation data for outcome prediction in pallidotomy for Parkinson´s disease
Author
Hamilton, Jennifer L. ; Micheli-Tzanakou, Evangelia ; Lehman, Richard M.
Author_Institution
Dept. of Biomed. Eng., Rutgers Univ., Piscataway, NJ, USA
Volume
1
fYear
2000
fDate
2000
Firstpage
1
Abstract
Neural networks were trained using the ALOPEX technique to predict the outcome of pallidotomy, an operation performed to alleviate Parkinson´s disease. Because of the limited number of operations performed, the training procedure relied heavily on simulation data. The assumptions from which the simulation data were derived were reflected in the performance of the resultant networks; the networks nonetheless retained the flexibility to respond appropriately to unusual inputs
Keywords
digital simulation; diseases; medical computing; neural nets; surgery; Parkinson´s disease; pallidotomy outcome prediction; simulation data-trained neural networks; surgical operation; training procedure; unusual inputs; Biological neural networks; Electrodes; Information analysis; Intelligent networks; Lesions; Neural networks; Optical recording; Parkinson´s disease; Predictive models; Surgery;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
Conference_Location
Chicago, IL
ISSN
1094-687X
Print_ISBN
0-7803-6465-1
Type
conf
DOI
10.1109/IEMBS.2000.900652
Filename
900652
Link To Document