Supervised machine learning model to predict mortality in patients undergoing venovenous extracorporeal membrane oxygenation from a nationwide multicentre registry.
Haeun LeeMyung Jin SongYoung-Jae ChoDong Jung KimSang-Bum HongSe Young JungSung Yoon LimPublished in: BMJ open respiratory research (2023)
ML prediction models outperformed previous mortality risk models. This model may be used to identify patients who are unlikely to benefit from VV-ECMO therapy during patient selection.
Keyphrases
- extracorporeal membrane oxygenation
- acute respiratory distress syndrome
- machine learning
- patients undergoing
- respiratory failure
- end stage renal disease
- ejection fraction
- newly diagnosed
- clinical trial
- cross sectional
- prognostic factors
- case report
- chronic kidney disease
- risk factors
- cardiovascular disease
- artificial intelligence
- peritoneal dialysis
- type diabetes
- cardiovascular events
- randomized controlled trial
- patient reported outcomes
- deep learning
- intensive care unit
- big data
- coronary artery disease