Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia.

Journal: BMC pulmonary medicine

PMID: 38956528

Abstract

AIM: To develop a decision-support tool for predicting extubation failure (EF) in neonates with bronchopulmonary dysplasia (BPD) using a set of machine-learning algorithms.

Authors

Yue Tao

Department of Radiology, Children's Hospital of Soochow University, Suzhou 215025, China.
Xin Ding

Department of Otorhinolaryngology Head and Neck Surgery, the Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wan-Liang Guo

Department of Radiology, Children's Hospital of Soochow University, Suzhou 215025, China.

Keywords

Airway Extubation Bronchopulmonary Dysplasia Decision Support Techniques Female Humans Infant, Newborn Logistic Models Machine Learning Male Nomograms Respiration, Artificial Retrospective Studies ROC Curve Treatment Failure

External Resources

View on PubMed Access via DOI PubMed (38956528)

Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia.

Abstract

Authors

Keywords

External Resources

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