Early prediction of need for invasive mechanical ventilation in the neonatal intensive care unit using artificial intelligence and electronic health records: a clinical study

Early prediction of need for invasive mechanical ventilation in the neonatal intensive care unit using artificial intelligence and electronic health records: a clinical study

Abstract Background Respiratory support is crucial for newborns with underdeveloped lung. The clinical outcomes of patients depend on the clinician’s ability to recognize the status underlying the presented symptoms and signs. With the increasing number of high-risk infants, artificial intelligence...

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Bibliographic Details
Main Authors: Younga Kim, Hyeongsub Kim, Jaewoo Choi, Kyungjae Cho, Dongjoon Yoo, Yeha Lee, Su Jeong Park, Mun Hui Jeong, Seong Hee Jeong, Kyung Hee Park, Shin-Yun Byun, Taehwa Kim, Sung-Ho Ahn, Woo Hyun Cho, Narae Lee
Format: Article
Language:English
Published: BMC 2023-10-01
Series:BMC Pediatrics
Subjects:
Deep learning
Neonatal intensive care
Newborn
Respiratory failure
Intubation
Online Access:https://doi.org/10.1186/s12887-023-04350-1

Internet

https://doi.org/10.1186/s12887-023-04350-1

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