Machine Learning Approach for the Prediction of In-Hospital Mortality in Traumatic Brain Injury Using Bio-Clinical Markers at Presentation to the Emergency Department.
Ahammed MekkodathilAyman El-MenyarMashhood NaduvilekandySandro RizoliHassan Al-ThaniPublished in: Diagnostics (Basel, Switzerland) (2023)
SVM was found to be the best-performing ML model in predicting the mortality of TBI patients. It had the highest AUC score and did not show overfitting, making it a more reliable model compared to LR, XgBoost, and RF.
Keyphrases
- traumatic brain injury
- emergency department
- machine learning
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- cardiovascular disease
- prognostic factors
- severe traumatic brain injury
- coronary artery disease
- type diabetes
- deep learning
- case report
- patient reported
- mild traumatic brain injury