Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury - Gravesteijn, Benjamin Y.; Lingsma, Hester F.; Nelson, David; Steyerberg, Ewout W.; Andreassen, Lasse; Anke, Audny; Audibert, Gérard; Barzó, Pál; Beauvais, Romuald; Bellander, Bo-Michael; Benali, Habib; Beretta, Luigi; et al. (Journal of clinical epidemiology, 2020)
Keywords: Adult; Algorithms; Artificial neural networks; Brain; Brain Injuries, Traumatic - therapy; Calibration; Cohort analysis; Cohort study; Coma; Confidence intervals; Data science; Datasets; Decision Making, Computer-Assisted; Epidemiology; Female; Glasgow Coma Scale; Head injuries; Human health and pathology; Humans; Internal Medicine; Laboratories; Learning algorithms; Life Sciences; Logistic Models; Machine Learning; Male; Medical disciplines: 700; Medical prognosis; Medical technology: 620; Medisinsk teknologi: 620; Medisinske Fag: 700; Middle Aged; Models, Statistical; Mortality; Neural networks; Neurosciences & behavior; Neurosciences & comportement; Prediction; Prediction models; Prognosis; Regression analysis; Regression models; Sciences sociales & comportementales, psychologie; Social & behavioral sciences, psychology; Support vector machines; Technology: 500; Teknologi: 500; Traumatic brain injury; Variables; VDP; Data science; Prognosis; Traumatic brain injury; Cohort study; Machine learning; Prediction; NN; LR; Gradient boosting machine; Glasgow coma scale; SVM; Support vector machine; Neural network; Random Forest; Logistic regression; GBM; RF; GCS; TBI; ML