Machine learning approach for predicting inhalation injury in patients with burns

The coronavirus disease pandemic has had a tangible impact on bronchoscopy for burn inpatients due to isolation and triage measures. We utilised the machine-learning approach to identify risk factors for predicting mild and severe inhalation injury and whether patients with burns experienced inhalat...

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Veröffentlicht in:	Burns 2023-11, Vol.49 (7), p.1592-1601
Hauptverfasser:	Yang, Shih-Yi, Huang, Chih-Jung, Yen, Cheng-I., Kao, Yu-Ching, Hsiao, Yen-Chang, Yang, Jui-Yung, Chang, Shu-Yin, Chuang, Shiow-Shuh, Chen, Hung-Chang
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence (AI) Bronchoscopy Burns Burns - complications Burns, Inhalation - complications Coronavirus disease (COVID-19) Gradient boosting-based machine learning (GBM) Hospitalization Humans Inhalation injury (INH) Machine Learning Pneumonia - complications Pneumonia - epidemiology Retrospective Studies
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