Machine Learning Algorithms to Predict Mortality of Neonates on Mechanical Intubation for Respiratory Failure.
Jen-Fu HsuChi YangChun-Yuan LinShih-Ming ChuHsuan-Rong HuangMing-Chou ChiangHsiao-Chin WangWei-Chao LiaoRei-Huei FuMing-Horng TsaiPublished in: Biomedicines (2021)
Machine learning algorithms increase the accuracy and predictive ability for mortality of neonates with respiratory failure compared with conventional neonatal illness severity scores. The RF model is suitable for clinical use in the NICU, and clinicians can gain insights and have better communication with families in advance.
Keyphrases
- respiratory failure
- machine learning
- extracorporeal membrane oxygenation
- mechanical ventilation
- artificial intelligence
- cardiovascular events
- big data
- low birth weight
- preterm infants
- deep learning
- risk factors
- acute respiratory distress syndrome
- cardiac arrest
- intensive care unit
- cardiovascular disease
- coronary artery disease