Machine Learning-Based Model for Predicting Prolonged Mechanical Ventilation in Patients with Congestive Heart Failure.
Le LiBin TuYulong XiongZhao HuZhenghao ZhangShangyu LiuYan YaoPublished in: Cardiovascular drugs and therapy (2022)
The present study developed and validated a CatBoost model, which could accurately predict PMV in mechanically ventilated patients with CHF. Moreover, this model has a favorable performance in predicting hospital mortality in these patients.
Keyphrases
- mechanical ventilation
- heart failure
- machine learning
- acute respiratory distress syndrome
- intensive care unit
- end stage renal disease
- ejection fraction
- healthcare
- chronic kidney disease
- newly diagnosed
- emergency department
- cardiovascular events
- cardiovascular disease
- peritoneal dialysis
- coronary artery disease
- patient reported outcomes
- atrial fibrillation
- respiratory failure
- deep learning