Decision Trees Regression: Decision tree regression uses a tree-like model to predict continuous numerical values and is ideal for use over logistic regression when categorical outcomes are not ...

The random forest model significantly outperformed all other models, including the logistic regression model that the entire paper focuses on, with an eventual AUC of 0.936 and an accuracy of 0.918.

The AUC for the prediction of ECE for this model was 0.85. Conclusions: This multivariate regression model based on clinical, biopsy & 3TmpMRI parameters have a high predictive value for pathology ECE ...

Novel nomogram models predict early neurological deterioration and 90-day outcomes in AIS patients treated with IV thrombolysis, helping healthcare professionals personalize treatment strategies.

Z. SU, G. ZHU, X. CHEN, Y YANG, Sparse envelope model: efficient estimation and response variable selection in multivariate linear regression, Biometrika, Vol. 103 ...

We concentrate on penalized methods that fit and shrink p predictors and in doing so, reduce the variance of the coefficient estimates. 27 Thus, these methods would improve the accuracy of the model.

The new score, based on a multivariate regression model, demonstrated superior predictive accuracy for both 28-day and 90-day mortalities, with Areas under the ROC curves of 0.863 and 0.853 ...