Web-based prediction of extubation outcome in premature infants on mechanical ventilation using an artificial neural network.
The web-based implementation of a decision-support tool for the prediction of extubation outcome in mechanically ventilated premature infants enables the integration of advanced and computationally intensive modeling approaches with easy-usage, no maintenance requirements and wide availability. Accordingly, the artificial neural network predictive tool developed provides decision-support in determining whether to extubate a premature infant to clinicians in NICUs anywhere with access to the Internet.
Mueller
Martina
M
Department of Biometry and Epidemiology, Medical University of South Carolina, Charleston, SC, USA.
Wagner
Carol L
CL
Annibale
David J
DJ
Hulsey
Thomas C
TC
Knapp
Rebecca G
RG
Almeida
Jonas S
JS
D003658:Decision Making, Computer-Assisted; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D020407:Internet; D016571:Neural Networks, Computer; D012121:Respiration, Artificial; D015300:Ventilator Weaning