DocumentCode
2229643
Title
Radial Basis Networks and Logistic Regression Method for Prediction of Broncho Pulmonary Dysplasia
Author
Wajs, Wieslaw ; Stoch, Pawel ; Kruczek, Piotr
Author_Institution
AGH Univ. of Sci. & Technol., Krakow
fYear
2007
fDate
20-24 Oct. 2007
Firstpage
551
Lastpage
555
Abstract
The main goal of this paper is prediction of Bronchopulmonary Dysplasia among newborn children. Static and dynamic parameters obtained from hospital database and medical data monitoring system were used to build logistic regression and radial basis function neural networks (RBFN) models.
Keywords
diseases; health care; medical administrative data processing; radial basis function networks; Bronchopulmonary Dysplasia prediction; hospital database; logistic regression method; medical data monitoring system; radial basis function neural networks models; Biomedical monitoring; Databases; Hospitals; Logistics; Lungs; Medical treatment; Pediatrics; Pulse measurements; Testing; Ventilation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2007. ISDA 2007. Seventh International Conference on
Conference_Location
Rio de Janeiro
Print_ISBN
978-0-7695-2976-9
Type
conf
DOI
10.1109/ISDA.2007.79
Filename
4389665
Link To Document