Predicting optimal endotracheal tube size and depth in pediatric patients using demographic data and machine learning techniques

Background Use of endotracheal tubes (ETTs) with appropriate size and depth can help minimize intubation-related complications in pediatric patients. Existing age-based formulae for selecting the optimal ETT size present several inaccuracies. We developed a machine learning model that predicts the o...

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Xehetasun bibliografikoak

Egile Nagusiak:	Hyeonsik Kim, Hyun-Kyu Yoon, Hyeonhoon Lee, Chul-Woo Jung, Hyung-Chul Lee
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Korean Society of Anesthesiologists 2023-12-01
Saila:	Korean Journal of Anesthesiology
Gaiak:	airway management demography general anesthesia intratracheal intubation machine learning pediatrics
Sarrera elektronikoa:	http://ekja.org/upload/pdf/kja-23501.pdf
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