title: Web-based prediction of extubation outcome in premature infants on mechanical ventilation using an artificial neural network.
abstract: 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.
authors.affiliation: Department of Biometry and Epidemiology, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Martina
authors.initials: M
authors.lastname: Mueller
authors.forename: Carol L
authors.initials: CL
authors.lastname: Wagner
authors.forename: David J
authors.initials: DJ
authors.lastname: Annibale
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Hulsey
authors.forename: Rebecca G
authors.initials: RG
authors.lastname: Knapp
authors.forename: Jonas S
authors.initials: JS
authors.lastname: Almeida
mesh_terms: 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