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.
fDate :
Aug. 30 2006-Sept. 3 2006
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;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.259349
