DocumentCode
471682
Title
Identifying risk factors for two complication types for neonatal intensive care patients (NICU)
Author
Frize, Monique ; Walker, RC ; Ibrahim, Doaa
Author_Institution
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, Ont.
fYear
2006
fDate
Aug. 30 2006-Sept. 3 2006
Firstpage
2324
Lastpage
2327
Abstract
This paper discusses the results of applying artificial neural networks to predicting complication for neonatal intensive care patients. Risk factors that lead to necrotizing entero-colitis or broncho-pulmonary dysplasia were identified. Future work will expand this work to other outcomes and add probability information to the estimations
Keywords
diseases; medical computing; medical information systems; obstetrics; patient care; risk analysis; NICU; artificial neural networks; broncho-pulmonary dysplasia; necrotizing entero-colitis; neonatal intensive care patients; risk factor identification; Artificial neural networks; Cellular neural networks; Cities and towns; Databases; Decision making; Medical diagnostic imaging; Pediatrics; Predictive models; USA Councils; Ventilation;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location
New York, NY
ISSN
1557-170X
Print_ISBN
1-4244-0032-5
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2006.259349
Filename
4462258
Link To Document