Machine Learning Models for Survival and Neurological Outcome Prediction of Out-of-Hospital Cardiac Arrest Patients.
Chi-Yung ChengI-Min ChiuWun-Huei ZengChih-Min TsaiChun-Hung Richard LinPublished in: BioMed research international (2021)
Prognostic models trained with ML technique showed appropriate calibration and high discrimination for survival and neurologic outcome of OHCA without using prehospital data, with XGB exhibiting the best performance.
Keyphrases
- machine learning
- end stage renal disease
- chronic kidney disease
- newly diagnosed
- ejection fraction
- big data
- cardiac arrest
- peritoneal dialysis
- prognostic factors
- free survival
- electronic health record
- artificial intelligence
- deep learning
- patient reported outcomes
- body composition
- patient reported
- blood brain barrier
- low cost
- data analysis