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Predicting extubation readiness in extreme preterm infants based on patterns of breathing.

, , , , , , and . SSCI, page 1-7. IEEE, (2017)

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Feature selection and oversampling in analysis of clinical data for extubation readiness in extreme preterm infants., , , , , and . EMBC, page 4427-4430. IEEE, (2015)Organizational principles of cloud storage to support collaborative biomedical research., , , , , , and . EMBC, page 1231-1234. IEEE, (2015)Undersampling and Bagging of Decision Trees in the Analysis of Cardiorespiratory Behavior for the Prediction of Extubation Readiness in Extremely Preterm Infants., , , , , , and . EMBC, page 4940-4944. IEEE, (2018)Correlation of clinical parameters with cardiorespiratory behavior in successfully extubated extremely preterm infants., , , , , , and . EMBC, page 4431-4434. IEEE, (2015)A semi-Markov chain approach to modeling respiratory patterns prior to extubation in preterm infants., , , , , , and . EMBC, page 2022-2026. IEEE, (2017)Comparison of Wired and Wireless Heart Rate Monitoring in the Neonatal Intensive Care Unit., , , , , , and . EMBC, page 1-4. IEEE, (2023)Prediction of extubation readiness in extreme preterm infants based on measures of cardiorespiratory variability., , , , , , , and . EMBC, page 5630-5633. IEEE, (2012)Predicting extubation readiness in extreme preterm infants based on patterns of breathing., , , , , , and . SSCI, page 1-7. IEEE, (2017)APEX_SCOPE: A graphical user interface for visualization of multi-modal data in inter-disciplinary studies., , , , , and . EMBC, page 2602-2605. IEEE, (2017)Detection of differences of cardiorespiratory metrics between non-invasive respiratory support modes using machine learning methods., , , , , , and . Biomed. Signal Process. Control., (August 2023)