Artificial intelligence in the NICU to predict extubation success in prematurely born infants
Objectives: Mechanical ventilation in prematurely born infants, particularly if prolonged, can cause long term complications including bronchopulmonary dysplasia. Timely extubation then is essential, yet predicting its success remains challenging. Artificial intelligence (AI) may provide a potential solution. Content: A narrative review was undertaken to explore AI’s role in predicting extubation success in prematurely born infants. Across the 11 studies analysed, the range of reported area under the receiver operator characteristic curve (AUC) for the selected prediction models was between 0.7 and 0.87. Only two studies implemented an external validation procedure. Comparison to the results of clinical predictors was made in two studies. One group reported a logistic regression model that outperformed clinical predictors on decision tree analysis, while another group reported clinical predictors outperformed their artificial neural network model (AUCs: ANN 0.68 vs. clinical predictors 0.86). Amongst the studies there was an heterogenous selection of variables for inclusion in prediction models, as well as variations in definitions of extubation failure. Summary: Although there is potential for AI to enhance extubation success, no model’s performance has yet surpassed that of clinical predictors. Outlook: Future studies should incorporate external validation to increase the applicability of the models to clinical settings.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Artificial intelligence in the NICU to predict extubation success in prematurely born infants ; volume:52 ; number:2 ; year:2024 ; pages:119-125 ; extent:07
Journal of perinatal medicine ; 52, Heft 2 (2024), 119-125 (gesamt 07)
- Creator
- DOI
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10.1515/jpm-2023-0454
- URN
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urn:nbn:de:101:1-2024020813094694238543
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:35 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Jenkinson, Allan C.
- Dassios, Theodore
- Greenough, Anne
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Diaphragmatic electromyography during a spontaneous breathing trial to predict extubation failure in preterm infants
Utilization of spontaneous breathing trial, objective cough test, and diaphragmatic ultrasound results to predict extubation success: COBRE-US trial
Handgrip strength to predict extubation outcome: a prospective multicenter trial
Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants
Neuroprotective therapies in the NICU in term infants: present and future
A pilot study of a new test to predict extubation failure
Accuracy of the spontaneous breathing trial using a combined CPAP + PSV model to predict extubation outcomes in very preterm infants
Nicus am Marktstr.
The DELUX study: development of lung volumes during extubation of preterm infants
The ratio of respiratory rate to diaphragm thickening fraction for predicting extubation success
Using Machine Learning to Predict Nosocomial Infections and Medical Accidents in a NICU
Predicting extubation success: still a conundrum?
Diaphragmatic electromyography during a spontaneous breathing trial to predict extubation failure in preterm infants
Utilization of spontaneous breathing trial, objective cough test, and diaphragmatic ultrasound results to predict extubation success: COBRE-US trial
Handgrip strength to predict extubation outcome: a prospective multicenter trial
Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants
Neuroprotective therapies in the NICU in term infants: present and future
A pilot study of a new test to predict extubation failure
Accuracy of the spontaneous breathing trial using a combined CPAP + PSV model to predict extubation outcomes in very preterm infants
Nicus am Marktstr.
The DELUX study: development of lung volumes during extubation of preterm infants
The ratio of respiratory rate to diaphragm thickening fraction for predicting extubation success